Overview

Brought to you by YData

Dataset statistics

Number of variables129
Number of observations26208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.0 MiB
Average record size in memory1.1 KiB

Variable types

DateTime1
Categorical128

Dataset

DescriptionSix-Month Monitoring Dataset from a 10-Turbine Onshore Wind Farm in Greece.
URLhttps://doi.org/10.5281/zenodo.14546479

Alerts

Gear Oil Temp. Avg. [°C] has constant value "0" Constant
Gear Bearing Temp. Avg. [°C] has constant value "0" Constant
Gear Oil TemperatureLevel2_3 Avg. [°C] has constant value "0" Constant
Ambient WindSpeed Estimated Avg. [m/s] has constant value "0" Constant
Grid Production PossibleInductive Avg. [var] has constant value "0" Constant
Grid Production PossibleInductive Max. [var] has constant value "0" Constant
Grid Production PossibleInductive Min. [var] has constant value "0" Constant
Grid Production PossibleInductive StdDev [var] has constant value "0" Constant
Grid Production PossibleCapacitive Avg. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Max. [var] has constant value "0" Constant
Grid Production PossibleCapacitive Min. [var] has constant value "0" Constant
Grid Production PossibleCapacitive StdDev [var] has constant value "0" Constant
Reactive power set point [var] has constant value "0" Constant
Spinner Temp. SlipRing Avg. [°C] has constant value "0" Constant
HourCounters Average Total Avg. [h] has constant value "0" Constant
Total hour counter [h] has constant value "0" Constant
Grid on hours [h] has constant value "0" Constant
Grid ok hours [h] has constant value "0" Constant
Turbine ok hours [h] has constant value "0" Constant
Run hours [h] has constant value "0" Constant
Generator 1 hours [h] has constant value "0" Constant
Generator 2 hours [h] has constant value "0" Constant
Yaw hours [h] has constant value "0" Constant
Service hours [h] has constant value "0" Constant
Ambient ok hours [h] has constant value "0" Constant
Wind ok hours [h] has constant value "0" Constant
Active power generator 0, Total accumulated [W] has constant value "0" Constant
Active power generator 1, Total accumulated [W] has constant value "0" Constant
Total Active power [W] has constant value "0" Constant
Reactive power generator 1, Total accumulated [var] has constant value "0" Constant
Reactive power generator 2, Total accumulated [var] has constant value "0" Constant
Active power limit source is highly overall correlated with Power factor set point and 1 other fieldsHigh correlation
Blades PitchAngle Min. [°] is highly overall correlated with Blades PitchAngle StdDev [°] and 1 other fieldsHigh correlation
Blades PitchAngle StdDev [°] is highly overall correlated with Blades PitchAngle Min. [°] and 2 other fieldsHigh correlation
Generator RPM Avg. [RPM] is highly overall correlated with Rotor RPM Avg. [RPM]High correlation
Generator RPM Max. [RPM] is highly overall correlated with Rotor RPM Max. [RPM]High correlation
Generator RPM Min. [RPM] is highly overall correlated with Rotor RPM Min. [RPM]High correlation
Generator RPM StdDev [RPM] is highly overall correlated with Rotor RPM StdDev [RPM]High correlation
Grid Production CosPhi Avg. is highly overall correlated with Production LatestAverage Active Power Gen 0 Avg. [W] and 1 other fieldsHigh correlation
Grid Production CurrentPhase1 Avg. [A] is highly overall correlated with Grid Production CurrentPhase2 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase2 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production CurrentPhase3 Avg. [A] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production PossiblePower Max. [W] is highly overall correlated with Grid Production Power Max. [W]High correlation
Grid Production PossiblePower Min. [W] is highly overall correlated with Grid Production Power Min. [W]High correlation
Grid Production PossiblePower StdDev [W] is highly overall correlated with Grid Production Power StdDev [W]High correlation
Grid Production Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Grid Production Power Max. [W] is highly overall correlated with Grid Production PossiblePower Max. [W]High correlation
Grid Production Power Min. [W] is highly overall correlated with Grid Production PossiblePower Min. [W]High correlation
Grid Production Power StdDev [W] is highly overall correlated with Grid Production PossiblePower StdDev [W]High correlation
Grid Production ReactivePower Avg. [W] is highly overall correlated with Blades PitchAngle Min. [°] and 8 other fieldsHigh correlation
Grid Production ReactivePower Max. [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production ReactivePower StdDev [W] is highly overall correlated with Grid Production ReactivePower Avg. [W]High correlation
Grid Production VoltagePhase1 Avg. [V] is highly overall correlated with Grid Production VoltagePhase2 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase2 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
Grid Production VoltagePhase3 Avg. [V] is highly overall correlated with Grid Production VoltagePhase1 Avg. [V] and 1 other fieldsHigh correlation
HourCounters Average AlarmActive Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average AmbientOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average Gen1 Avg. [h] is highly overall correlated with HourCounters Average Gen2 Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average Gen2 Avg. [h] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 4 other fieldsHigh correlation
HourCounters Average GridOk Avg. [h] is highly overall correlated with HourCounters Average AmbientOk Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average Run Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 2 other fieldsHigh correlation
HourCounters Average ServiceOn Avg. [h] is highly overall correlated with HourCounters Average GridOk Avg. [h] and 1 other fieldsHigh correlation
HourCounters Average TurbineOk Avg. [h] is highly overall correlated with HourCounters Average AlarmActive Avg. [h] and 3 other fieldsHigh correlation
Power factor set point is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Power factor set point source is highly overall correlated with Active power limit source and 1 other fieldsHigh correlation
Production LatestAverage Active Power Gen 0 Avg. [W] is highly overall correlated with Grid Production CosPhi Avg. and 3 other fieldsHigh correlation
Production LatestAverage Active Power Gen 1 Avg. [W] is highly overall correlated with HourCounters Average Gen1 Avg. [h]High correlation
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly overall correlated with Grid Production CosPhi Avg. and 4 other fieldsHigh correlation
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly overall correlated with Production LatestAverage Total Reactive Power Avg. [var]High correlation
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly overall correlated with Blades PitchAngle StdDev [°] and 2 other fieldsHigh correlation
Production LatestAverage Total Active Power Avg. [W] is highly overall correlated with Grid Production CurrentPhase1 Avg. [A] and 4 other fieldsHigh correlation
Production LatestAverage Total Reactive Power Avg. [var] is highly overall correlated with Grid Production ReactivePower Avg. [W] and 2 other fieldsHigh correlation
Rotor RPM Avg. [RPM] is highly overall correlated with Generator RPM Avg. [RPM]High correlation
Rotor RPM Max. [RPM] is highly overall correlated with Generator RPM Max. [RPM]High correlation
Rotor RPM Min. [RPM] is highly overall correlated with Generator RPM Min. [RPM]High correlation
Rotor RPM StdDev [RPM] is highly overall correlated with Generator RPM StdDev [RPM]High correlation
Generator RPM Max. [RPM] is highly imbalanced (60.8%) Imbalance
Generator RPM Min. [RPM] is highly imbalanced (53.9%) Imbalance
Generator RPM Avg. [RPM] is highly imbalanced (54.5%) Imbalance
Generator RPM StdDev [RPM] is highly imbalanced (56.8%) Imbalance
Generator Bearing Temp. Avg. [°C] is highly imbalanced (77.2%) Imbalance
Generator Phase1 Temp. Avg. [°C] is highly imbalanced (73.3%) Imbalance
Generator Phase2 Temp. Avg. [°C] is highly imbalanced (76.8%) Imbalance
Generator Phase3 Temp. Avg. [°C] is highly imbalanced (73.2%) Imbalance
Generator SlipRing Temp. Avg. [°C] is highly imbalanced (51.2%) Imbalance
Generator Bearing2 Temp. Avg. [°C] is highly imbalanced (78.3%) Imbalance
Hydraulic Oil Temp. Avg. [°C] is highly imbalanced (76.9%) Imbalance
Gear Oil TemperatureBasis Avg. [°C] is highly imbalanced (62.8%) Imbalance
Gear Bearing TemperatureHSRotorEnd Avg. [°C] is highly imbalanced (73.1%) Imbalance
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C] is highly imbalanced (69.4%) Imbalance
Gear Bearing TemperatureHSMiddle Avg. [°C] is highly imbalanced (67.2%) Imbalance
Gear Bearing TemperatureHollowShaftRotor Avg. [°C] is highly imbalanced (53.5%) Imbalance
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C] is highly imbalanced (61.6%) Imbalance
Nacelle Temp. Avg. [°C] is highly imbalanced (62.4%) Imbalance
Rotor RPM Max. [RPM] is highly imbalanced (55.4%) Imbalance
Rotor RPM Avg. [RPM] is highly imbalanced (59.5%) Imbalance
Ambient WindSpeed Max. [m/s] is highly imbalanced (90.0%) Imbalance
Ambient WindSpeed Min. [m/s] is highly imbalanced (85.6%) Imbalance
Ambient WindSpeed Avg. [m/s] is highly imbalanced (91.4%) Imbalance
Ambient WindSpeed StdDev [m/s] is highly imbalanced (68.9%) Imbalance
Ambient WindDir Relative Avg. [°] is highly imbalanced (82.5%) Imbalance
Ambient WindDir Absolute Avg. [°] is highly imbalanced (85.7%) Imbalance
Grid InverterPhase1 Temp. Avg. [°C] is highly imbalanced (60.6%) Imbalance
Grid RotorInvPhase1 Temp. Avg. [°C] is highly imbalanced (50.4%) Imbalance
Grid Production Power Avg. [W] is highly imbalanced (77.4%) Imbalance
Grid Production CosPhi Avg. is highly imbalanced (71.4%) Imbalance
Grid Production Frequency Avg. [Hz] is highly imbalanced (95.9%) Imbalance
Grid Production VoltagePhase1 Avg. [V] is highly imbalanced (92.5%) Imbalance
Grid Production VoltagePhase2 Avg. [V] is highly imbalanced (92.3%) Imbalance
Grid Production VoltagePhase3 Avg. [V] is highly imbalanced (91.7%) Imbalance
Grid Production CurrentPhase1 Avg. [A] is highly imbalanced (77.8%) Imbalance
Grid Production CurrentPhase2 Avg. [A] is highly imbalanced (75.6%) Imbalance
Grid Production CurrentPhase3 Avg. [A] is highly imbalanced (76.9%) Imbalance
Grid Production Power Max. [W] is highly imbalanced (71.0%) Imbalance
Grid Production Power Min. [W] is highly imbalanced (69.5%) Imbalance
Grid Busbar Temp. Avg. [°C] is highly imbalanced (51.1%) Imbalance
Grid Production Power StdDev [W] is highly imbalanced (75.5%) Imbalance
Grid Production ReactivePower Avg. [W] is highly imbalanced (57.6%) Imbalance
Grid Production PossiblePower Avg. [W] is highly imbalanced (82.0%) Imbalance
Grid Production PossiblePower Max. [W] is highly imbalanced (78.4%) Imbalance
Grid Production PossiblePower Min. [W] is highly imbalanced (78.0%) Imbalance
Grid Production PossiblePower StdDev [W] is highly imbalanced (79.6%) Imbalance
Active power limit [W] is highly imbalanced (97.8%) Imbalance
Active power limit source is highly imbalanced (99.9%) Imbalance
Power factor set point is highly imbalanced (99.9%) Imbalance
Power factor set point source is highly imbalanced (99.9%) Imbalance
Controller Ground Temp. Avg. [°C] is highly imbalanced (90.2%) Imbalance
Controller Top Temp. Avg. [°C] is highly imbalanced (80.1%) Imbalance
Controller Hub Temp. Avg. [°C] is highly imbalanced (74.1%) Imbalance
Controller VCP Temp. Avg. [°C] is highly imbalanced (63.2%) Imbalance
Controller VCP ChokecoilTemp. Avg. [°C] is highly imbalanced (75.1%) Imbalance
Spinner Temp. Avg. [°C] is highly imbalanced (68.5%) Imbalance
Blades PitchAngle Min. [°] is highly imbalanced (50.4%) Imbalance
Blades PitchAngle Max. [°] is highly imbalanced (55.8%) Imbalance
Blades PitchAngle Avg. [°] is highly imbalanced (57.9%) Imbalance
Blades PitchAngle StdDev [°] is highly imbalanced (51.5%) Imbalance
HVTrafo Phase1 Temp. Avg. [°C] is highly imbalanced (84.4%) Imbalance
HVTrafo Phase2 Temp. Avg. [°C] is highly imbalanced (81.7%) Imbalance
HVTrafo Phase3 Temp. Avg. [°C] is highly imbalanced (83.9%) Imbalance
HVTrafo AirOutlet Temp. Avg. [°C] is highly imbalanced (53.7%) Imbalance
HourCounters Average GridOn Avg. [h] is highly imbalanced (99.3%) Imbalance
HourCounters Average GridOk Avg. [h] is highly imbalanced (98.3%) Imbalance
HourCounters Average TurbineOk Avg. [h] is highly imbalanced (97.4%) Imbalance
HourCounters Average Run Avg. [h] is highly imbalanced (95.9%) Imbalance
HourCounters Average Gen1 Avg. [h] is highly imbalanced (80.9%) Imbalance
HourCounters Average Gen2 Avg. [h] is highly imbalanced (62.9%) Imbalance
HourCounters Average ServiceOn Avg. [h] is highly imbalanced (98.5%) Imbalance
HourCounters Average AmbientOk Avg. [h] is highly imbalanced (96.1%) Imbalance
HourCounters Average WindOk Avg. [h] is highly imbalanced (66.4%) Imbalance
HourCounters Average AlarmActive Avg. [h] is highly imbalanced (95.8%) Imbalance
Production LatestAverage Active Power Gen 0 Avg. [W] is highly imbalanced (70.2%) Imbalance
Production LatestAverage Active Power Gen 1 Avg. [W] is highly imbalanced (83.3%) Imbalance
Production LatestAverage Active Power Gen 2 Avg. [W] is highly imbalanced (75.5%) Imbalance
Production LatestAverage Total Active Power Avg. [W] is highly imbalanced (78.6%) Imbalance
Production LatestAverage Reactive Power Gen 0 Avg. [var] is highly imbalanced (67.1%) Imbalance
Production LatestAverage Reactive Power Gen 1 Avg. [var] is highly imbalanced (56.5%) Imbalance
Production LatestAverage Reactive Power Gen 2 Avg. [var] is highly imbalanced (58.3%) Imbalance
Active power generator 2, Total accumulated [W] is highly imbalanced (99.9%) Imbalance
Reactive power generator 0,Total accumulated [var] is highly imbalanced (95.6%) Imbalance
Total reactive power [var] is highly imbalanced (95.1%) Imbalance
Timestamp has unique values Unique

Reproduction

Analysis started2025-05-14 17:37:20.986669
Analysis finished2025-05-14 17:37:50.334882
Duration29.35 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Timestamp
Date

Unique 

Distinct26208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Minimum2020-01-01 00:00:00
Maximum2020-06-30 23:50:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-14T19:37:50.375197image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T19:37:50.459582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Generator RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24189 
1
 
2019

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Length

2025-05-14T19:37:50.534352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:50.571586image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Most occurring characters

ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24189
92.3%
1 2019
 
7.7%

Generator RPM Min. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23654 
1
2554 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Length

2025-05-14T19:37:50.754732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:50.790854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Most occurring characters

ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23654
90.3%
1 2554
 
9.7%

Generator RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23699 
1
2509 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Length

2025-05-14T19:37:50.835767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:50.872122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Most occurring characters

ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23699
90.4%
1 2509
 
9.6%

Generator RPM StdDev [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23881 
1
 
2327

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Length

2025-05-14T19:37:50.916175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:50.953821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Most occurring characters

ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23881
91.1%
1 2327
 
8.9%

Generator Bearing Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25238 
1
 
970

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Length

2025-05-14T19:37:50.997710image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.033145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25238
96.3%
1 970
 
3.7%

Generator Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25014 
1
 
1194

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Length

2025-05-14T19:37:51.077300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.113102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25014
95.4%
1 1194
 
4.6%

Generator Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25217 
1
 
991

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Length

2025-05-14T19:37:51.155087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.191894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25217
96.2%
1 991
 
3.8%

Generator Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25008 
1
 
1200

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%

Length

2025-05-14T19:37:51.233911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.269357image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25008
95.4%
1 1200
 
4.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23430 
1
2778 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%

Length

2025-05-14T19:37:51.313176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.349607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23430
89.4%
1 2778
 
10.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25302 
1
 
906

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%

Length

2025-05-14T19:37:51.395025image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.430670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25302
96.5%
1 906
 
3.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22335 
1
3873 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Length

2025-05-14T19:37:51.472949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.511860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Most occurring characters

ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22335
85.2%
1 3873
 
14.8%

Hydraulic Oil Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25226 
1
 
982

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Length

2025-05-14T19:37:51.556994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.593052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring characters

ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25226
96.3%
1 982
 
3.7%

Gear Oil Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:51.636939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.670096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Gear Bearing Temp. Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:51.709522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.744277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24329 
1
 
1879

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Length

2025-05-14T19:37:51.783324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.818969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring characters

ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24329
92.8%
1 1879
 
7.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23204 
1
3004 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%

Length

2025-05-14T19:37:51.863471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.900333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23204
88.5%
1 3004
 
11.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:51.944411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:51.979283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25005 
1
 
1203

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%

Length

2025-05-14T19:37:52.018699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.055171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%

Most occurring characters

ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25005
95.4%
1 1203
 
4.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24776 
1
 
1432

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Length

2025-05-14T19:37:52.099501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.135258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24776
94.5%
1 1432
 
5.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24633 
1
 
1575

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%

Length

2025-05-14T19:37:52.177732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.215475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%

Most occurring characters

ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24633
94.0%
1 1575
 
6.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23617 
1
2591 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%

Length

2025-05-14T19:37:52.257943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.294419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%

Most occurring characters

ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23617
90.1%
1 2591
 
9.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24247 
1
 
1961

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Length

2025-05-14T19:37:52.340655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.376277image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Most occurring characters

ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24247
92.5%
1 1961
 
7.5%

Nacelle Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24304 
1
 
1904

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Length

2025-05-14T19:37:52.418649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.456100image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Most occurring characters

ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24304
92.7%
1 1904
 
7.3%

Rotor RPM Max. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23771 
1
2437 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Length

2025-05-14T19:37:52.498393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.535062image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Most occurring characters

ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23771
90.7%
1 2437
 
9.3%

Rotor RPM Min. [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23107 
1
3101 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Length

2025-05-14T19:37:52.581659image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.618263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Most occurring characters

ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23107
88.2%
1 3101
 
11.8%

Rotor RPM Avg. [RPM]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24088 
1
 
2120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Length

2025-05-14T19:37:52.662550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.700809image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Most occurring characters

ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24088
91.9%
1 2120
 
8.1%

Rotor RPM StdDev [RPM]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23071 
1
3137 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Length

2025-05-14T19:37:52.745120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.781295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Most occurring characters

ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23071
88.0%
1 3137
 
12.0%

Ambient WindSpeed Max. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25869 
1
 
339

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Length

2025-05-14T19:37:52.827310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.863105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25869
98.7%
1 339
 
1.3%

Ambient WindSpeed Min. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25671 
1
 
537

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Length

2025-05-14T19:37:52.905820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:52.943288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25671
98.0%
1 537
 
2.0%

Ambient WindSpeed Avg. [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25924 
1
 
284

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Length

2025-05-14T19:37:52.985536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.021296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring characters

ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25924
98.9%
1 284
 
1.1%

Ambient WindSpeed StdDev [m/s]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24744 
1
 
1464

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Length

2025-05-14T19:37:53.065335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.101148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Most occurring characters

ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24744
94.4%
1 1464
 
5.6%

Ambient WindDir Relative Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25523 
1
 
685

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Length

2025-05-14T19:37:53.143649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.181313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Most occurring characters

ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25523
97.4%
1 685
 
2.6%

Ambient WindDir Absolute Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25676 
1
 
532

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%

Length

2025-05-14T19:37:53.224073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.260213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%

Most occurring characters

ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25676
98.0%
1 532
 
2.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22485 
1
3723 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%

Length

2025-05-14T19:37:53.304092image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.340570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%

Most occurring characters

ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22485
85.8%
1 3723
 
14.2%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:53.384820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.419761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24169 
1
 
2039

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%

Length

2025-05-14T19:37:53.599875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.635635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%

Most occurring characters

ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24169
92.2%
1 2039
 
7.8%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23361 
1
2847 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%

Length

2025-05-14T19:37:53.678828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.715341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%

Most occurring characters

ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23361
89.1%
1 2847
 
10.9%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23194 
1
3014 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%

Length

2025-05-14T19:37:53.759504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.797704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%

Most occurring characters

ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23194
88.5%
1 3014
 
11.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22395 
1
3813 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Length

2025-05-14T19:37:53.842187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.878609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Most occurring characters

ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22395
85.5%
1 3813
 
14.5%

Grid Production Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25254 
1
 
954

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Length

2025-05-14T19:37:53.924737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:53.960332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25254
96.4%
1 954
 
3.6%

Grid Production CosPhi Avg.
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24898 
1
 
1310

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Length

2025-05-14T19:37:54.002503image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.039730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring characters

ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24898
95.0%
1 1310
 
5.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26092 
1
 
116

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Length

2025-05-14T19:37:54.081819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.118004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26092
99.6%
1 116
 
0.4%

Grid Production VoltagePhase1 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25967 
1
 
241

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Length

2025-05-14T19:37:54.163200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.198933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring characters

ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25967
99.1%
1 241
 
0.9%

Grid Production VoltagePhase2 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25959 
1
 
249

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Length

2025-05-14T19:37:54.242894image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.278719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25959
99.0%
1 249
 
1.0%

Grid Production VoltagePhase3 Avg. [V]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25937 
1
 
271

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Length

2025-05-14T19:37:54.320746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.358402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Most occurring characters

ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25937
99.0%
1 271
 
1.0%

Grid Production CurrentPhase1 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25271 
1
 
937

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Length

2025-05-14T19:37:54.400867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.436467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Most occurring characters

ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25271
96.4%
1 937
 
3.6%

Grid Production CurrentPhase2 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25149 
1
 
1059

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Length

2025-05-14T19:37:54.480482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.516227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25149
96.0%
1 1059
 
4.0%

Grid Production CurrentPhase3 Avg. [A]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25224 
1
 
984

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Length

2025-05-14T19:37:54.558528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.596550image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring characters

ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25224
96.2%
1 984
 
3.8%

Grid Production Power Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24873 
1
 
1335

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Length

2025-05-14T19:37:54.638885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.674532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Most occurring characters

ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24873
94.9%
1 1335
 
5.1%

Grid Production Power Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24778 
1
 
1430

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Length

2025-05-14T19:37:54.718766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.754542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Most occurring characters

ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24778
94.5%
1 1430
 
5.5%

Grid Busbar Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23421 
1
2787 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Length

2025-05-14T19:37:54.796650image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.834819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Most occurring characters

ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23421
89.4%
1 2787
 
10.6%

Grid Production Power StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25147 
1
 
1061

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Length

2025-05-14T19:37:54.879369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.915480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Grid Production ReactivePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23946 
1
 
2262

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Length

2025-05-14T19:37:54.959693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:54.996243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23946
91.4%
1 2262
 
8.6%

Grid Production ReactivePower Max. [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22735 
1
3473 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Length

2025-05-14T19:37:55.040385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.078263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring characters

ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22735
86.7%
1 3473
 
13.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22674 
1
3534 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Length

2025-05-14T19:37:55.122813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.159187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Most occurring characters

ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22674
86.5%
1 3534
 
13.5%

Grid Production ReactivePower StdDev [W]
Categorical

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22047 
1
4161 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Length

2025-05-14T19:37:55.205510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.242004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Most occurring characters

ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22047
84.1%
1 4161
 
15.9%

Grid Production PossiblePower Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25497 
1
 
711

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Length

2025-05-14T19:37:55.286370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.323647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring characters

ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25497
97.3%
1 711
 
2.7%

Grid Production PossiblePower Max. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25306 
1
 
902

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Length

2025-05-14T19:37:55.366240image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.402050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25306
96.6%
1 902
 
3.4%

Grid Production PossiblePower Min. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25283 
1
 
925

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Length

2025-05-14T19:37:55.446900image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.482645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring characters

ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25283
96.5%
1 925
 
3.5%

Grid Production PossiblePower StdDev [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25370 
1
 
838

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%

Length

2025-05-14T19:37:55.524791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.562408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%

Most occurring characters

ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25370
96.8%
1 838
 
3.2%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.605994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.639689image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.680839image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.714485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.754246image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.789525image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.829055image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.862497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.903695image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:55.937220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:55.976034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.010877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:56.050070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.083370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:56.124406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.157730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Active power limit [W]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26151 
1
 
57

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Length

2025-05-14T19:37:56.197276image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.234633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26151
99.8%
1 57
 
0.2%

Active power limit source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:37:56.417404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.452877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Reactive power set point [var]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:56.496549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.530080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Power factor set point
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:37:56.569554image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.607350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Power factor set point source
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26206 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Length

2025-05-14T19:37:56.649768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.685700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26206
> 99.9%
1 2
 
< 0.1%

Controller Ground Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25877 
1
 
331

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Length

2025-05-14T19:37:56.729770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.765404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Most occurring characters

ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25877
98.7%
1 331
 
1.3%

Controller Top Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25395 
1
 
813

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Length

2025-05-14T19:37:56.807400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.844799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring characters

ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25395
96.9%
1 813
 
3.1%

Controller Hub Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25062 
1
 
1146

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Length

2025-05-14T19:37:56.887484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:56.923585image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Most occurring characters

ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25062
95.6%
1 1146
 
4.4%

Controller VCP Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24358 
1
 
1850

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%

Length

2025-05-14T19:37:56.967485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.003238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24358
92.9%
1 1850
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25123 
1
 
1085

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Length

2025-05-14T19:37:57.047634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.083605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring characters

ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25123
95.9%
1 1085
 
4.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22574 
1
3634 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Length

2025-05-14T19:37:57.125847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.163865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Most occurring characters

ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22574
86.1%
1 3634
 
13.9%

Spinner Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24718 
1
 
1490

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Length

2025-05-14T19:37:57.208658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.244538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Most occurring characters

ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24718
94.3%
1 1490
 
5.7%

Spinner Temp. SlipRing Avg. [°C]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:57.288969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.322571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Blades PitchAngle Min. [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23362 
1
2846 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Length

2025-05-14T19:37:57.361863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.399827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Most occurring characters

ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23362
89.1%
1 2846
 
10.9%

Blades PitchAngle Max. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23803 
1
2405 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Length

2025-05-14T19:37:57.444558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.481041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring characters

ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23803
90.8%
1 2405
 
9.2%

Blades PitchAngle Avg. [°]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23967 
1
 
2241

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Length

2025-05-14T19:37:57.527325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.564037image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Most occurring characters

ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23967
91.4%
1 2241
 
8.6%

Blades PitchAngle StdDev [°]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23456 
1
2752 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

Length

2025-05-14T19:37:57.608915image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.647475image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

Most occurring characters

ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23456
89.5%
1 2752
 
10.5%

HVTrafo Phase1 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25617 
1
 
591

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

Length

2025-05-14T19:37:57.692348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.728442image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

Most occurring characters

ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25617
97.7%
1 591
 
2.3%

HVTrafo Phase2 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25479 
1
 
729

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

Length

2025-05-14T19:37:57.772701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.808662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

Most occurring characters

ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25479
97.2%
1 729
 
2.8%

HVTrafo Phase3 Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25591 
1
 
617

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

Length

2025-05-14T19:37:57.850965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.888580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

Most occurring characters

ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25591
97.6%
1 617
 
2.4%

HVTrafo AirOutlet Temp. Avg. [°C]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23637 
1
2571 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%

Length

2025-05-14T19:37:57.932582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:57.969674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%

Most occurring characters

ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23637
90.2%
1 2571
 
9.8%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:58.016666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.050664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26193 
1
 
15

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Length

2025-05-14T19:37:58.089898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.127320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26193
99.9%
1 15
 
0.1%

HourCounters Average GridOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26167 
1
 
41

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Length

2025-05-14T19:37:58.169701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.205502image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring characters

ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26167
99.8%
1 41
 
0.2%

HourCounters Average TurbineOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26140 
1
 
68

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

Length

2025-05-14T19:37:58.249764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.285667image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

Most occurring characters

ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26140
99.7%
1 68
 
0.3%

HourCounters Average Run Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26091 
1
 
117

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

Length

2025-05-14T19:37:58.328184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.365588image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26091
99.6%
1 117
 
0.4%

HourCounters Average Gen1 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25441 
1
 
767

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

Length

2025-05-14T19:37:58.408148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.445046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

Most occurring characters

ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25441
97.1%
1 767
 
2.9%

HourCounters Average Gen2 Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24337 
1
 
1871

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%

Length

2025-05-14T19:37:58.489402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.525492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%

Most occurring characters

ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24337
92.9%
1 1871
 
7.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22939 
1
3269 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

Length

2025-05-14T19:37:58.567991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.607871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

Most occurring characters

ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22939
87.5%
1 3269
 
12.5%

HourCounters Average ServiceOn Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26172 
1
 
36

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

Length

2025-05-14T19:37:58.653165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.689294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

Most occurring characters

ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26172
99.9%
1 36
 
0.1%

HourCounters Average AmbientOk Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26097 
1
 
111

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Length

2025-05-14T19:37:58.734732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.770811image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring characters

ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26097
99.6%
1 111
 
0.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24581 
1
 
1627

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

Length

2025-05-14T19:37:58.813398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.850898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

Most occurring characters

ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24581
93.8%
1 1627
 
6.2%

HourCounters Average AlarmActive Avg. [h]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26089 
1
 
119

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Length

2025-05-14T19:37:58.893953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:58.930289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26089
99.5%
1 119
 
0.5%

Total hour counter [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:58.974432image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.007819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid on hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.047385image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.082924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Grid ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.122314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.155757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Turbine ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.197375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.376444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Run hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.415429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.448905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 1 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.490011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.523146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Generator 2 hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.563999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.597446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Yaw hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.637248image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.672514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Service hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.712233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.745937image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Ambient ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.786991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.820671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Wind ok hours [h]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:37:59.860199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.895468image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Production LatestAverage Active Power Gen 0 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24824 
1
 
1384

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Length

2025-05-14T19:37:59.935406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:37:59.971073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Most occurring characters

ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24824
94.7%
1 1384
 
5.3%

Production LatestAverage Active Power Gen 1 Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25559 
1
 
649

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%

Length

2025-05-14T19:38:00.015546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.052340image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%

Most occurring characters

ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25559
97.5%
1 649
 
2.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25147 
1
 
1061

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Length

2025-05-14T19:38:00.094574image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.131974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring characters

ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25147
96.0%
1 1061
 
4.0%

Production LatestAverage Total Active Power Avg. [W]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
25320 
1
 
888

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Length

2025-05-14T19:38:00.174757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.210904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Most occurring characters

ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 25320
96.6%
1 888
 
3.4%

Production LatestAverage Reactive Power Gen 0 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
24627 
1
 
1581

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Length

2025-05-14T19:38:00.255261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.291205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Most occurring characters

ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24627
94.0%
1 1581
 
6.0%

Production LatestAverage Reactive Power Gen 1 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23860 
1
 
2348

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Length

2025-05-14T19:38:00.333671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.371709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Most occurring characters

ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23860
91.0%
1 2348
 
9.0%

Production LatestAverage Reactive Power Gen 2 Avg. [var]
Categorical

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
23999 
1
 
2209

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%

Length

2025-05-14T19:38:00.416512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.453338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%

Most occurring characters

ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 23999
91.6%
1 2209
 
8.4%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
22287 
1
3921 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%

Length

2025-05-14T19:38:00.499538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.536264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%

Most occurring characters

ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 22287
85.0%
1 3921
 
15.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:38:00.581403image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.617064image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:38:00.656924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.690691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26207 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Length

2025-05-14T19:38:00.731885image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.767834image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26207
> 99.9%
1 1
 
< 0.1%

Total Active power [W]
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:38:00.810184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.845254image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26083 
1
 
125

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%

Length

2025-05-14T19:38:00.884664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.920737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%

Most occurring characters

ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26083
99.5%
1 125
 
0.5%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:38:00.964848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:00.998368image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26208 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26208
100.0%

Length

2025-05-14T19:38:01.037699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:01.072733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26208
100.0%

Most occurring characters

ValueCountFrequency (%)
0 26208
100.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26208
100.0%

Total reactive power [var]
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.5 MiB
0
26063 
1
 
145

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters26208
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Length

2025-05-14T19:38:01.112242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T19:38:01.148007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Most occurring characters

ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 26063
99.4%
1 145
 
0.6%

Correlations

2025-05-14T19:38:01.274317image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Active power generator 2, Total accumulated [W]Active power limit [W]Active power limit sourceAmbient Temp. Avg. [°C]Ambient WindDir Absolute Avg. [°]Ambient WindDir Relative Avg. [°]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed StdDev [m/s]Blades PitchAngle Avg. [°]Blades PitchAngle Max. [°]Blades PitchAngle Min. [°]Blades PitchAngle StdDev [°]Controller Ground Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Generator Bearing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator RPM Avg. [RPM]Generator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM StdDev [RPM]Generator SlipRing Temp. Avg. [°C]Grid Busbar Temp. Avg. [°C]Grid InverterPhase1 Temp. Avg. [°C]Grid Production CosPhi Avg.Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Frequency Avg. [Hz]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production Power Avg. [W]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HourCounters Average AlarmActive Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average Yaw Avg. [h]Hydraulic Oil Temp. Avg. [°C]Nacelle Temp. Avg. [°C]Power factor set pointPower factor set point sourceProduction LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Total Reactive Power Avg. [var]Reactive power generator 0,Total accumulated [var]Rotor RPM Avg. [RPM]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM StdDev [RPM]Spinner Temp. Avg. [°C]Total reactive power [var]
Active power generator 2, Total accumulated [W]1.0000.0000.0000.0010.0000.0000.0000.0000.0000.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0140.0000.0100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0040.0000.000
Active power limit [W]0.0001.0000.1400.0160.0000.0350.0000.0110.0180.0000.0000.0000.0000.0130.0570.0000.0050.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0000.0000.0000.0500.0740.0140.0000.0000.0000.0110.0000.0070.0000.0010.0140.0070.0080.0000.0000.0030.0000.0050.0000.0240.0180.0070.0120.0000.0100.0050.0000.0000.0040.0060.0000.0080.0050.0000.0000.0000.1000.1170.0000.0000.1950.4270.0520.1640.1180.0160.0060.0000.0000.1400.1400.0230.0000.0040.0160.0120.0000.0100.0000.0130.0130.0000.0000.0180.0100.035
Active power limit source0.0000.1401.0000.0000.0000.0110.0000.0000.0130.0000.0000.0000.0000.0000.0180.0060.0090.0070.0000.0000.0040.0030.0060.0000.0000.0000.0000.0080.0080.0000.0290.0080.0060.0000.0000.0000.0000.0000.0000.0000.0050.0080.0070.0080.0320.0000.0000.0000.0000.0080.0050.0040.0070.0000.0150.0000.0000.0210.0210.0200.0000.0000.0000.0000.0120.0100.0110.0970.0000.0000.0000.0000.2740.0000.1760.0000.0000.0000.0080.0000.7500.7500.0270.0000.0000.0030.0000.0000.0340.0000.0000.0000.0000.0000.0000.0040.087
Ambient Temp. Avg. [°C]0.0010.0160.0001.0000.0140.0200.0270.0180.0000.0000.0260.0210.0190.0180.0000.0080.0000.0090.0000.0070.0030.0140.0070.0180.0160.0140.0190.0000.0000.0000.0000.0000.0050.0230.0140.0230.0180.0230.0130.0000.0220.0140.0140.0170.0080.0200.0160.0180.0150.0250.0160.0120.0170.0260.0200.0120.0130.0020.0000.0000.0000.0010.0070.0110.0050.0000.0000.0160.0130.0040.0220.0080.0000.0130.0150.0130.0230.0120.0100.0220.0000.0000.0380.0110.0000.0320.0000.0160.0210.0140.0000.0280.0130.0120.0140.0180.000
Ambient WindDir Absolute Avg. [°]0.0000.0000.0000.0141.0000.1310.0250.0270.0090.0000.0290.0290.0190.0120.0000.0230.0000.0000.0000.0090.0080.0180.0140.0170.0160.0000.0080.0000.0000.0000.0000.0000.0000.0230.0240.0240.0160.0010.0000.0000.0290.0140.0000.0180.0000.0000.0100.0000.0120.0130.0260.0000.0000.0310.0270.0050.0240.0000.0000.0000.0200.0110.0080.0170.0000.0000.0000.0110.0000.0000.0230.0000.0000.0110.0000.0090.0550.0200.0000.0080.0000.0000.0360.0040.0000.0400.0090.0110.0050.0140.0000.0250.0190.0260.0140.0090.000
Ambient WindDir Relative Avg. [°]0.0000.0350.0110.0200.1311.0000.0150.0170.0000.0130.0770.0930.0470.0470.0050.0120.0000.0110.0000.0020.0000.0040.0000.0130.0270.0000.0390.0000.0000.0000.0080.0000.0050.0640.0850.0620.0500.0000.0120.0000.0540.0070.0010.0000.0000.0000.0000.0080.0000.0090.0070.0000.0000.0760.0500.0360.0250.0000.0000.0000.0000.0000.0000.0070.0000.0000.0100.0650.0650.0100.0600.0630.0510.0660.0480.0690.0270.0120.0070.0280.0110.0110.0800.0000.0080.0940.0220.0240.0060.0400.0000.0830.0750.0490.0420.0140.000
Ambient WindSpeed Avg. [m/s]0.0000.0000.0000.0270.0250.0151.0000.1230.1110.0120.1400.0380.0550.0330.0000.0000.0000.0060.0000.0040.0740.0670.0530.0670.0530.0430.0030.0000.0100.0000.0140.0090.0120.1230.0880.0830.0600.0000.0130.0360.0460.2050.1980.1970.0000.2350.1080.0910.0610.1950.0940.0810.0520.0430.0520.0600.0220.0140.0170.0000.0210.0410.0170.0070.0000.0000.0000.0000.0000.0390.0670.0000.0000.0000.0000.0000.0440.0000.0000.0030.0000.0000.0470.1080.0990.0370.0000.0150.1930.0310.0000.1180.0770.0770.0480.0000.007
Ambient WindSpeed Max. [m/s]0.0000.0110.0000.0180.0270.0170.1231.0000.0340.0650.0570.0540.0280.0280.0000.0000.0000.0000.0000.0120.0370.0350.0270.0340.0130.0180.0070.0000.0060.0120.0170.0120.0050.0620.0840.0320.0490.0140.0000.0260.0340.0900.0870.0880.0000.0810.1180.0480.0720.0870.0880.0500.0640.0320.0350.0280.0340.0000.0000.0000.0290.0250.0140.0050.0000.0000.0050.0000.0000.0040.0270.0000.0000.0000.0000.0000.0460.0210.0000.0000.0000.0000.0350.0480.0330.0340.0000.0120.0860.0250.0000.0520.0800.0260.0410.0040.000
Ambient WindSpeed Min. [m/s]0.0000.0180.0130.0000.0090.0000.1110.0341.0000.0490.0990.0300.0930.0900.0000.0020.0000.0180.0000.0270.0350.0270.0430.0310.0360.0360.0000.0020.0080.0000.0110.0000.0140.0990.0450.1340.0780.0040.0180.0260.0350.0860.0950.0920.0160.0940.0320.1440.0510.0860.0410.1220.0540.0810.0800.0930.0760.0000.0000.0000.0320.0240.0210.0140.0050.0000.0100.0000.0070.0840.0920.0170.0470.0000.0000.0090.0390.0000.0000.0000.0130.0130.0550.0660.0880.0400.0250.0560.0840.0640.0000.0910.0460.1190.0660.0000.000
Ambient WindSpeed StdDev [m/s]0.0000.0000.0000.0000.0000.0130.0120.0650.0491.0000.0670.0020.0560.0980.0000.0070.0130.0040.0070.0160.0210.0280.0170.0120.0170.0000.0120.0050.0170.0000.0170.0240.0230.0480.0440.0260.0930.0000.0090.0240.0290.0450.0490.0510.0000.0470.0440.0440.1500.0490.0510.0460.1460.0490.0560.0640.0530.0000.0000.0000.0170.0210.0100.0130.0000.0000.0000.0000.0000.0130.0340.0000.0100.0000.0000.0000.0020.0560.0110.0050.0000.0000.0380.0100.0350.0320.0000.0400.0480.0280.0000.0480.0330.0220.0790.0070.000
Blades PitchAngle Avg. [°]0.0000.0000.0000.0260.0290.0770.1400.0570.0990.0671.0000.2360.3950.4290.0090.0100.0000.0250.0070.0370.0150.0450.0160.1060.1230.0130.0130.0100.0130.0220.0160.0120.0060.2290.2060.2270.2130.0350.0690.0190.2960.1540.1700.1940.0000.2240.1850.2180.2430.2060.1780.1480.2690.4140.3020.2110.2400.0030.0110.0000.0480.0510.0350.0090.0090.0280.0320.1690.1410.1710.3750.0720.0290.1690.0790.1010.0970.0870.0140.0050.0000.0000.3360.0920.2560.3210.1080.2620.2150.3110.0230.2560.1880.1880.1710.0250.042
Blades PitchAngle Max. [°]0.0000.0000.0000.0210.0290.0930.0380.0540.0300.0020.2361.0000.0990.1010.0090.0000.0150.0020.0070.0000.0240.0290.0070.0530.0630.0000.0880.0000.0000.0000.0070.0040.0000.0840.2540.0570.0610.0100.0100.0190.2520.0930.1040.1150.0000.1480.1410.1160.1630.1170.1210.0620.1240.1780.1440.0420.0830.0000.0000.0000.0000.0000.0000.0080.0160.0160.0070.1010.0980.0090.1700.0520.0160.0980.0680.0680.1730.0270.0000.0120.0000.0000.2180.0000.0970.2310.0280.0830.1240.1330.0050.0880.2220.0500.0550.0280.015
Blades PitchAngle Min. [°]0.0000.0000.0000.0190.0190.0470.0550.0280.0930.0560.3950.0991.0000.5500.0000.0070.0000.0370.0000.0340.0370.0520.0330.0890.1010.0270.0000.0070.0210.0260.0070.0200.0000.1850.1370.3130.2070.0300.0490.0040.2940.0850.0900.1110.0000.1280.1010.1310.1540.1300.0920.0880.1870.5130.3910.3140.3530.0000.0000.0000.0360.0450.0340.0170.0280.0200.0330.1300.1030.2600.4390.0490.0130.1300.0480.0670.1020.0360.0110.0070.0000.0000.3480.1620.2150.3130.1830.3740.1420.3860.0280.2050.1150.2700.1460.0000.055
Blades PitchAngle StdDev [°]0.0050.0130.0000.0180.0120.0470.0330.0280.0900.0980.4290.1010.5501.0000.0000.0150.0000.0000.0160.0210.0100.0400.0000.0600.0720.0020.0040.0000.0000.0110.0000.0000.0010.1800.1450.2500.3970.0290.0580.0000.3200.1070.1150.1320.0000.1710.1540.2440.2320.1530.1230.1630.2730.5240.3910.2970.4570.0090.0000.0010.0270.0220.0150.0120.0180.0260.0400.1370.1240.2690.4410.0570.0360.1330.0520.0740.0990.0930.0130.0170.0000.0000.3340.1650.2650.3200.1850.5280.1630.3770.0710.1990.1230.2010.3220.0110.101
Controller Ground Temp. Avg. [°C]0.0000.0570.0180.0000.0000.0050.0000.0000.0000.0000.0090.0090.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0080.0120.0000.0000.0040.0000.0000.0070.0000.0000.0090.0000.0010.0000.0070.0030.0000.0090.0000.0000.0000.0000.0000.0050.0190.0000.0150.0000.0000.0000.0000.0110.0000.0080.0000.0000.0000.0000.0000.0000.0280.0350.0530.0000.0000.0770.1190.0250.0920.0780.0000.0030.0000.0140.0180.0180.0140.0000.0000.0070.0090.0000.0120.0000.0000.0000.0060.0000.0060.0110.000
Controller Hub Temp. Avg. [°C]0.0000.0000.0060.0080.0230.0120.0000.0000.0020.0070.0100.0000.0070.0150.0001.0000.0220.0020.0210.0000.0000.0000.0000.0180.0000.0200.0000.0100.0040.0110.0000.0000.0000.0110.0190.0250.0160.0050.0260.0090.0110.0260.0250.0180.0000.0000.0000.0150.0000.0110.0100.0230.0050.0360.0160.0370.0270.0000.0000.0000.0170.0030.0000.0180.0070.0130.0000.0160.0120.0430.0410.0050.0020.0140.0000.0000.0000.0000.0040.0000.0060.0060.0230.0180.0310.0270.0000.0290.0140.0180.0000.0120.0070.0080.0190.0590.000
Controller Top Temp. Avg. [°C]0.0000.0050.0090.0000.0000.0000.0000.0000.0000.0130.0000.0150.0000.0000.0000.0221.0000.0020.0540.0000.0000.0000.0000.0040.0040.0100.0130.0170.0110.0030.0000.0000.0120.0000.0110.0000.0000.0000.0000.0040.0000.0000.0000.0000.0010.0000.0000.0000.0000.0030.0000.0000.0110.0000.0000.0000.0080.0000.0000.0000.0000.0100.0000.0040.0000.0000.0030.0450.0400.0000.0000.0400.0070.0390.0370.0360.0110.0000.0050.0220.0090.0090.0070.0000.0000.0000.0000.0000.0000.0000.0000.0100.0200.0000.0000.0170.000
Controller VCP ChokecoilTemp. Avg. [°C]0.0000.0000.0070.0090.0000.0110.0060.0000.0180.0040.0250.0020.0370.0000.0000.0020.0021.0000.0000.0270.0410.0220.0260.0280.0000.0270.0090.0390.0340.0470.0390.0500.0290.0100.0000.0000.0140.0240.0000.0220.0140.0090.0140.0070.0000.0060.0050.0080.0070.0000.0200.0070.0000.0000.0070.0000.0060.0000.0000.0000.0320.0240.0350.0080.0330.0240.0310.0000.0000.0410.0140.0000.0030.0070.0000.0000.0150.0000.0110.0000.0070.0070.0150.0330.0060.0250.0110.0040.0000.0000.0040.0130.0000.0060.0210.0000.007
Controller VCP Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0070.0070.0070.0000.0160.0000.0210.0540.0001.0000.0000.0000.0150.0120.0310.0320.0080.0010.0140.0000.0000.0000.0090.0200.0200.0060.0190.0270.0670.0400.0040.0120.0000.0000.0000.0000.0030.0220.0000.0150.0040.0080.0000.0150.0120.0080.0090.0310.0130.0040.0120.0140.0090.0000.0000.0000.0220.0000.0170.0060.0000.0120.0000.0000.0130.0000.0090.0000.0000.0090.0410.0000.0000.0140.0060.0070.0110.0250.0290.0000.0210.0000.0210.0080.0110.0310.0200.000
Controller VCP WaterTemp. Avg. [°C]0.0000.0000.0000.0070.0090.0020.0040.0120.0270.0160.0370.0000.0340.0210.0000.0000.0000.0270.0001.0000.0510.0480.0210.0360.0240.0310.0060.0400.0350.3320.0680.0610.0700.0220.0250.0210.0190.0130.0250.1610.0200.0180.0200.0140.0090.0000.0000.0090.0000.0110.0000.0140.0070.0240.0080.0340.0000.0000.0000.0000.2470.2610.3370.0090.0260.0180.0170.0080.0000.0080.0260.0000.0000.0060.0000.0090.0150.0070.0310.0090.0000.0000.0280.0000.0050.0240.0140.0090.0140.0060.0000.0200.0240.0260.0080.0000.005
Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]0.0000.0000.0040.0030.0080.0000.0740.0370.0350.0210.0150.0240.0370.0100.0000.0000.0000.0410.0000.0511.0000.2630.2470.1940.0980.2110.0450.0700.0520.0320.0870.0820.0820.1230.0690.0650.0810.0180.0060.0710.0450.0850.0800.0840.0000.0780.0800.0170.0340.0840.0730.0330.0260.0250.0360.0380.0440.0000.0000.0000.0590.0780.0510.0000.0060.0140.0000.0600.0390.0020.0180.0040.0000.0580.0000.0110.0350.0120.0350.0000.0040.0040.0560.0550.0070.0480.0090.0000.0910.0180.0000.0990.0690.0640.0860.0000.000
Gear Bearing TemperatureHSMiddle Avg. [°C]0.0000.0000.0030.0140.0180.0040.0670.0350.0270.0280.0450.0290.0520.0400.0000.0000.0000.0220.0150.0480.2631.0000.1400.2300.1780.1790.0310.0830.0760.0420.0710.0880.0760.1360.0900.0960.1000.0130.0340.0620.0440.0750.0610.0720.0000.0710.0730.0390.0380.0680.0700.0320.0410.0600.0400.0360.0340.0000.0000.0000.0750.0730.0440.0020.0070.0000.0050.0580.0440.0180.0600.0000.0000.0560.0080.0160.0240.0000.0360.0000.0030.0030.0860.0590.0000.0840.0200.0270.0680.0310.0000.1480.0900.1050.0930.0120.018
Gear Bearing TemperatureHSRotorEnd Avg. [°C]0.0000.0000.0060.0070.0140.0000.0530.0270.0430.0170.0160.0070.0330.0000.0000.0000.0000.0260.0120.0210.2470.1401.0000.1350.1090.1870.0520.0590.0220.0240.0620.0700.0510.1470.0600.0740.0980.0000.0070.0350.0260.0760.0690.0750.0000.0560.0730.0220.0410.0680.0580.0350.0410.0180.0370.0580.0320.0000.0000.0000.0400.0460.0220.0060.0090.0260.0130.0650.0460.0310.0150.0020.0000.0630.0000.0140.0210.0230.0130.0050.0060.0060.0380.0300.0330.0320.0090.0000.0680.0190.0000.1300.0700.0790.0850.0150.000
Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]0.0000.0000.0000.0180.0170.0130.0670.0340.0310.0120.1060.0530.0890.0600.0100.0180.0040.0280.0310.0360.1940.2300.1351.0000.2780.2610.0370.0990.1120.0310.0660.0580.0610.1980.0960.1500.1210.0280.0660.0280.0670.0480.0480.0510.0000.0600.0720.0400.0370.0590.0610.0200.0400.0750.0660.0700.0680.0000.0000.0000.0310.0390.0400.0030.0050.0000.0000.0530.0360.0220.0920.0000.0000.0510.0030.0170.0120.0000.0280.0000.0000.0000.1090.0460.0120.0990.0060.0370.0590.0710.0000.2110.1010.1390.1080.0140.016
Gear Bearing TemperatureHollowShaftRotor Avg. [°C]0.0000.0060.0000.0160.0160.0270.0530.0130.0360.0170.1230.0630.1010.0720.0000.0000.0040.0000.0320.0240.0980.1780.1090.2781.0000.1210.0380.0860.1330.0290.0430.0320.0170.2090.1020.1610.1110.0170.0670.0160.0740.0370.0320.0410.0000.0490.0670.0380.0520.0430.0550.0170.0510.0990.0650.0840.0600.0000.0030.0000.0150.0280.0290.0000.0030.0050.0090.0700.0500.0340.1110.0160.0000.0690.0300.0370.0080.0000.0270.0030.0000.0000.1310.0300.0170.1250.0270.0440.0430.0990.0000.2280.1030.1470.0900.0250.006
Gear Oil TemperatureBasis Avg. [°C]0.0000.0000.0000.0140.0000.0000.0430.0180.0360.0000.0130.0000.0270.0020.0000.0200.0100.0270.0080.0310.2110.1790.1870.2610.1211.0000.0480.0980.0670.0320.0490.0640.0770.1450.0700.0570.0940.0200.0260.0070.0080.0270.0270.0300.0000.0350.0260.0060.0060.0310.0230.0110.0100.0000.0230.0280.0120.0000.0000.0000.0240.0320.0300.0100.0000.0150.0000.0140.0110.0000.0190.0000.0000.0120.0100.0000.0000.0000.0200.0180.0000.0000.0350.0170.0000.0230.0000.0000.0330.0090.0000.1230.0830.0710.0810.0190.005
Gear Oil TemperatureLevel1 Avg. [°C]0.0000.0000.0000.0190.0080.0390.0030.0070.0000.0120.0130.0880.0000.0040.0080.0000.0130.0090.0010.0060.0450.0310.0520.0370.0380.0481.0000.0180.0210.0110.0280.0140.0090.0430.0660.0090.0350.0200.0360.0080.0480.0140.0040.0100.0000.0160.0100.0070.0040.0140.0090.0220.0000.0130.0170.0000.0070.0000.0060.0000.0170.0070.0100.0120.0170.0080.0000.0330.0230.0070.0160.0060.0000.0320.0200.0270.0340.0070.0060.0100.0000.0000.0380.0090.0100.0410.0360.0080.0160.0000.0000.0420.0500.0270.0220.0210.000
Generator Bearing Temp. Avg. [°C]0.0000.0000.0080.0000.0000.0000.0000.0000.0020.0050.0100.0000.0070.0000.0120.0100.0170.0390.0140.0400.0700.0830.0590.0990.0860.0980.0181.0000.2190.0380.0940.0990.0880.0450.0090.0270.0280.0130.0450.0120.0070.0060.0100.0040.0000.0170.0020.0000.0000.0090.0010.0060.0000.0000.0000.0000.0000.0070.0030.0000.0190.0250.0490.0120.0170.0000.0140.0000.0000.0090.0000.0000.0000.0000.0000.0000.0090.0050.0230.0180.0080.0080.0140.0000.0230.0110.0000.0080.0050.0000.0000.0430.0100.0250.0190.0110.000
Generator Bearing2 Temp. Avg. [°C]0.0000.0000.0080.0000.0000.0000.0100.0060.0080.0170.0130.0000.0210.0000.0000.0040.0110.0340.0000.0350.0520.0760.0220.1120.1330.0670.0210.2191.0000.0240.0890.0730.0690.0330.0000.0260.0060.0000.0350.0230.0040.0000.0020.0000.0000.0110.0060.0100.0000.0060.0080.0000.0000.0080.0140.0100.0060.0030.0010.0130.0170.0370.0350.0040.0360.0370.0260.0090.0000.0210.0200.0000.0000.0050.0030.0000.0040.0050.0100.0000.0080.0080.0070.0120.0130.0030.0000.0000.0070.0020.0100.0360.0000.0320.0000.0220.000
Generator CoolingWater Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0000.0120.0000.0000.0220.0000.0260.0110.0000.0110.0030.0470.0000.3320.0320.0420.0240.0310.0290.0320.0110.0380.0241.0000.0560.0440.0490.0190.0130.0150.0090.0230.0310.1240.0260.0060.0050.0050.0080.0000.0000.0000.0000.0060.0050.0000.0000.0210.0110.0220.0000.0000.0000.0000.2050.2360.3030.0150.0350.0290.0120.0000.0000.0120.0200.0000.0000.0000.0000.0000.0300.0080.0210.0070.0000.0000.0180.0000.0000.0190.0000.0120.0000.0170.0000.0120.0180.0170.0020.0000.000
Generator Phase1 Temp. Avg. [°C]0.0000.0500.0290.0000.0000.0080.0140.0170.0110.0170.0160.0070.0070.0000.0040.0000.0000.0390.0000.0680.0870.0710.0620.0660.0430.0490.0280.0940.0890.0561.0000.3480.2820.0340.0240.0250.0220.0000.0080.0730.0250.0400.0480.0600.0000.0130.0120.0010.0220.0440.0560.0410.0120.0250.0240.0370.0040.0090.0000.0040.0780.0830.0680.0180.0140.0080.0120.0180.0070.0120.0000.0000.0120.0100.0000.0000.0250.0120.0000.0020.0290.0290.0350.0000.0000.0420.0480.0110.0380.0040.0000.0400.0120.0280.0230.0090.000
Generator Phase2 Temp. Avg. [°C]0.0000.0740.0080.0000.0000.0000.0090.0120.0000.0240.0120.0040.0200.0000.0000.0000.0000.0500.0090.0610.0820.0880.0700.0580.0320.0640.0140.0990.0730.0440.3481.0000.4230.0270.0260.0060.0190.0000.0000.0620.0120.0410.0470.0540.0020.0260.0150.0000.0280.0560.0530.0410.0140.0220.0270.0400.0000.0190.0080.0130.0790.0800.0610.0190.0210.0100.0090.0140.0030.0000.0000.0000.0050.0070.0000.0100.0240.0090.0000.0000.0080.0080.0230.0110.0000.0350.0400.0140.0450.0000.0070.0270.0170.0220.0190.0100.005
Generator Phase3 Temp. Avg. [°C]0.0000.0140.0060.0050.0000.0050.0120.0050.0140.0230.0060.0000.0000.0010.0000.0000.0120.0290.0200.0700.0820.0760.0510.0610.0170.0770.0090.0880.0690.0490.2820.4231.0000.0310.0220.0060.0240.0000.0040.1020.0110.0400.0580.0580.0000.0250.0120.0030.0240.0430.0690.0380.0220.0170.0160.0380.0160.0130.0180.0070.0940.0960.0690.0070.0140.0000.0010.0180.0030.0130.0000.0000.0000.0160.0000.0000.0200.0000.0000.0120.0060.0060.0300.0050.0000.0350.0490.0120.0460.0100.0000.0220.0100.0230.0130.0280.000
Generator RPM Avg. [RPM]0.0000.0000.0000.0230.0230.0640.1230.0620.0990.0480.2290.0840.1850.1800.0070.0110.0000.0100.0200.0220.1230.1360.1470.1980.2090.1450.0430.0450.0330.0190.0340.0270.0311.0000.3660.3670.4840.0190.0570.0000.1780.1550.1600.1650.0000.1600.1570.1420.1780.1660.1630.0910.1860.2040.1610.1870.1450.0040.0100.0000.0270.0290.0260.0000.0000.0170.0050.1510.1370.0560.2120.0510.0090.1520.0560.0710.0260.0360.0000.0180.0000.0000.2560.0530.1100.2570.0240.1110.1740.1660.0380.7540.3470.3350.4150.0370.050
Generator RPM Max. [RPM]0.0000.0000.0000.0140.0240.0850.0880.0840.0450.0440.2060.2540.1370.1450.0000.0190.0110.0000.0060.0250.0690.0900.0600.0960.1020.0700.0660.0090.0000.0130.0240.0260.0220.3661.0000.1450.3180.0100.0460.0170.1570.1140.1320.1310.0000.1440.1650.1360.1890.1260.1670.0880.1540.1670.1420.0900.0800.0000.0070.0020.0330.0350.0330.0000.0000.0140.0000.0980.0990.0670.1800.0550.0000.1020.0600.0790.0270.0290.0120.0120.0000.0000.1750.0000.1600.1920.0180.1090.1340.1110.0000.3190.7960.1140.2400.0270.006
Generator RPM Min. [RPM]0.0000.0000.0000.0230.0240.0620.0830.0320.1340.0260.2270.0570.3130.2500.0000.0250.0000.0000.0190.0210.0650.0960.0740.1500.1610.0570.0090.0270.0260.0150.0250.0060.0060.3670.1451.0000.2830.0390.0890.0120.2500.1020.1090.1160.0000.1080.0600.1480.0710.1340.0700.1390.1050.3040.2730.3050.2200.0000.0000.0000.0330.0290.0220.0080.0150.0260.0340.1030.0780.1930.3910.0170.0150.1020.0160.0400.1260.0220.0110.0050.0000.0000.3550.1630.1270.3160.0420.2410.1360.2380.0430.3840.1360.7800.2160.0280.068
Generator RPM StdDev [RPM]0.0060.0110.0000.0180.0160.0500.0600.0490.0780.0930.2130.0610.2070.3970.0090.0160.0000.0140.0270.0190.0810.1000.0980.1210.1110.0940.0350.0280.0060.0090.0220.0190.0240.4840.3180.2831.0000.0290.0410.0000.2290.1290.1350.1400.0050.1640.1580.2310.2240.1490.1410.1790.2420.1940.1680.1880.2590.0000.0000.0000.0250.0240.0140.0130.0000.0130.0000.1090.1020.0160.2040.0430.0230.1110.0370.0540.0450.0990.0000.0270.0000.0000.2370.0140.1520.2380.0100.2830.1590.1370.0550.4550.2920.2460.7000.0350.077
Generator SlipRing Temp. Avg. [°C]0.0000.0000.0000.0230.0010.0000.0000.0140.0040.0000.0350.0100.0300.0290.0000.0050.0000.0240.0670.0130.0180.0130.0000.0280.0170.0200.0200.0130.0000.0230.0000.0000.0000.0190.0100.0390.0291.0000.0630.0080.0280.0030.0000.0060.0000.0180.0100.0350.0180.0140.0130.0250.0190.0270.0250.0330.0260.0100.0000.0000.0090.0140.0250.0060.0260.0060.0200.0000.0000.0120.0350.0000.0000.0000.0000.0000.0200.0240.0100.0460.0000.0000.0220.0140.0150.0200.0260.0360.0090.0370.0000.0250.0070.0330.0370.0130.000
Grid Busbar Temp. Avg. [°C]0.0000.0070.0000.0130.0000.0120.0130.0000.0180.0090.0690.0100.0490.0580.0010.0260.0000.0000.0400.0250.0060.0340.0070.0660.0670.0260.0360.0450.0350.0310.0080.0000.0040.0570.0460.0890.0410.0631.0000.0000.0530.0190.0240.0270.0000.0370.0160.0600.0300.0310.0110.0280.0270.0530.0520.0440.0460.0000.0000.0000.0280.0130.0320.0200.0290.0190.0200.0000.0050.0620.0930.0000.0000.0000.0000.0000.0210.0180.0000.0530.0000.0000.0560.0530.0460.0530.0000.0690.0350.0430.0170.0600.0390.0690.0290.0170.021
Grid InverterPhase1 Temp. Avg. [°C]0.0000.0000.0000.0000.0000.0000.0360.0260.0260.0240.0190.0190.0040.0000.0000.0090.0040.0220.0040.1610.0710.0620.0350.0280.0160.0070.0080.0120.0230.1240.0730.0620.1020.0000.0170.0120.0000.0080.0001.0000.0000.0680.0840.0770.0000.0320.0190.0050.0130.0580.0660.0490.0150.0140.0090.0290.0200.0000.0000.0000.3300.2300.1400.0000.0010.0000.0000.0380.0320.0000.0110.0000.0000.0370.0080.0100.0060.0000.0350.0000.0000.0000.0060.0260.0000.0180.0150.0230.0540.0000.0060.0000.0130.0100.0000.0000.004
Grid Production CosPhi Avg.0.0000.0010.0050.0220.0290.0540.0460.0340.0350.0290.2960.2520.2940.3200.0070.0110.0000.0140.0120.0200.0450.0440.0260.0670.0740.0080.0480.0070.0040.0260.0250.0120.0110.1780.1570.2500.2290.0280.0530.0001.0000.1840.1920.2190.0000.2340.2050.2470.2150.2480.2390.1800.2540.4620.3350.2390.3160.0000.0000.0000.0210.0230.0300.0200.0000.0000.0150.1470.1400.0110.4880.0730.0270.1490.0790.1030.2800.0750.0130.0190.0050.0050.5930.0050.2140.5630.0500.4110.2600.3240.0490.1980.1410.1990.1780.0300.081
Grid Production CurrentPhase1 Avg. [A]0.0000.0140.0080.0140.0140.0070.2050.0900.0860.0450.1540.0930.0850.1070.0030.0260.0000.0090.0000.0180.0850.0750.0760.0480.0370.0270.0140.0060.0000.0060.0400.0410.0400.1550.1140.1020.1290.0030.0190.0680.1841.0000.7300.7080.0000.5340.2300.2620.2250.6270.3130.3400.2780.1890.1380.1350.1330.0160.0170.0190.0440.0390.0260.0000.0050.0100.0000.1870.1720.0750.1160.0310.0160.1800.0450.0730.1590.0600.0000.0110.0080.0080.2290.1950.3190.2210.0000.0620.6110.1240.0000.1640.1040.0890.1080.0150.004
Grid Production CurrentPhase2 Avg. [A]0.0000.0070.0070.0140.0000.0010.1980.0870.0950.0490.1700.1040.0900.1150.0000.0250.0000.0140.0000.0200.0800.0610.0690.0480.0320.0270.0040.0100.0020.0050.0480.0470.0580.1600.1320.1090.1350.0000.0240.0840.1920.7301.0000.7130.0000.5450.2410.2800.2480.6270.3370.3500.2980.2340.1530.1590.1590.0100.0180.0170.0530.0430.0310.0050.0000.0070.0000.1720.1610.0720.1380.0230.0140.1650.0360.0640.1280.0640.0000.0090.0070.0070.2290.1870.3410.2720.0020.0720.6180.1580.0040.1710.1160.0950.1130.0180.006
Grid Production CurrentPhase3 Avg. [A]0.0000.0080.0080.0170.0180.0000.1970.0880.0920.0510.1940.1150.1110.1320.0090.0180.0000.0070.0000.0140.0840.0720.0750.0510.0410.0300.0100.0040.0000.0050.0600.0540.0580.1650.1310.1160.1400.0060.0270.0770.2190.7080.7131.0000.0000.5740.2710.3010.2700.6890.3550.3670.3360.2260.1530.1410.1570.0120.0060.0130.0490.0400.0270.0030.0070.0010.0000.1880.1710.0770.1680.0300.0150.1810.0440.0710.1210.0660.0000.0070.0080.0080.2700.1930.3760.2630.0000.0840.6720.1570.0020.1790.1150.1030.1150.0120.005
Grid Production Frequency Avg. [Hz]0.0000.0000.0320.0080.0000.0000.0000.0000.0160.0000.0000.0000.0000.0000.0000.0000.0010.0000.0000.0090.0000.0000.0000.0000.0000.0000.0000.0000.0000.0080.0000.0020.0000.0000.0000.0000.0050.0000.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0060.0060.0120.0000.0000.0000.0000.0000.0000.0000.0060.0000.0000.0010.0000.0080.0000.0000.0000.0000.0000.0000.0020.0320.0320.0000.0000.0020.0000.0080.0000.0000.0000.0000.0000.0060.0000.0000.0000.000
Grid Production PossiblePower Avg. [W]0.0000.0000.0000.0200.0000.0000.2350.0810.0940.0470.2240.1480.1280.1710.0000.0000.0000.0060.0030.0000.0780.0710.0560.0600.0490.0350.0160.0170.0110.0000.0130.0260.0250.1600.1440.1080.1640.0180.0370.0320.2340.5340.5450.5740.0001.0000.3570.4100.3880.6530.3110.2960.3680.1590.1540.0650.1240.0000.0100.0000.0180.0220.0160.0000.0000.0120.0140.0990.0920.0650.2220.0000.0000.1000.0000.0040.1240.0600.0220.0130.0000.0000.1960.2690.4260.1720.0230.1360.6500.1140.0020.1700.1300.0980.1410.0070.005
Grid Production PossiblePower Max. [W]0.0000.0030.0000.0160.0100.0000.1080.1180.0320.0440.1850.1410.1010.1540.0000.0000.0000.0050.0220.0000.0800.0730.0730.0720.0670.0260.0100.0020.0060.0000.0120.0150.0120.1570.1650.0600.1580.0100.0160.0190.2050.2300.2410.2710.0000.3571.0000.2670.3580.2880.6500.1820.3000.1410.1290.0500.1270.0000.0000.0000.0080.0200.0000.0130.0030.0090.0000.1230.1150.0490.1730.0000.0060.1240.0000.0330.0550.0550.0470.0070.0000.0000.1690.0920.2360.1560.0060.1180.2930.1000.0060.1570.1500.0480.1740.0220.003
Grid Production PossiblePower Min. [W]0.0000.0000.0000.0180.0000.0080.0910.0480.1440.0440.2180.1160.1310.2440.0000.0150.0000.0080.0000.0090.0170.0390.0220.0400.0380.0060.0070.0000.0100.0000.0010.0000.0030.1420.1360.1480.2310.0350.0600.0050.2470.2620.2800.3010.0000.4100.2671.0000.2850.3330.2580.5410.3220.1540.1210.0650.1790.0110.0130.0080.0080.0100.0180.0000.0000.0000.0220.0650.0590.0750.2170.0000.0000.0660.0000.0000.0700.0780.0000.0110.0000.0000.1670.1190.3000.1620.0030.2370.3430.1070.0000.1510.1170.1310.2000.0110.000
Grid Production PossiblePower StdDev [W]0.0000.0050.0000.0150.0120.0000.0610.0720.0510.1500.2430.1630.1540.2320.0000.0000.0000.0070.0150.0000.0340.0380.0410.0370.0520.0060.0040.0000.0000.0000.0220.0280.0240.1780.1890.0710.2240.0180.0300.0130.2150.2250.2480.2700.0000.3880.3580.2851.0000.3020.2910.2030.7400.1790.1860.0900.1460.0000.0080.0000.0000.0160.0150.0000.0070.0000.0280.1090.1070.0610.2140.0020.0070.1100.0000.0000.0690.0840.0100.0150.0000.0000.1880.0990.2780.1820.0500.1430.3130.1460.0090.1740.1690.0630.1970.0170.001
Grid Production Power Avg. [W]0.0140.0000.0080.0250.0130.0090.1950.0870.0860.0490.2060.1170.1300.1530.0050.0110.0030.0000.0040.0110.0840.0680.0680.0590.0430.0310.0140.0090.0060.0060.0440.0560.0430.1660.1260.1340.1490.0140.0310.0580.2480.6270.6270.6890.0000.6530.2880.3330.3021.0000.3830.3780.3810.2140.1450.1300.1490.0080.0040.0100.0360.0340.0210.0000.0000.0130.0070.1940.1740.0780.1890.0300.0150.1870.0450.0720.1230.0730.0150.0160.0080.0080.3090.2670.4320.2520.0050.1150.8540.1530.0000.1760.1110.1220.1310.0070.008
Grid Production Power Max. [W]0.0000.0240.0050.0160.0260.0070.0940.0880.0410.0510.1780.1210.0920.1230.0190.0100.0000.0200.0080.0000.0730.0700.0580.0610.0550.0230.0090.0010.0080.0050.0560.0530.0690.1630.1670.0700.1410.0130.0110.0660.2390.3130.3370.3550.0000.3110.6500.2580.2910.3831.0000.2500.3370.1870.1560.0740.1320.0070.0110.0010.0370.0250.0060.0000.0170.0030.0000.1250.1280.0300.1740.0320.0110.1210.0350.0820.0450.0510.0220.0000.0050.0050.2090.0600.2520.2210.0190.0950.3670.1240.0080.1700.1460.0560.1520.0020.012
Grid Production Power Min. [W]0.0100.0180.0040.0120.0000.0000.0810.0500.1220.0460.1480.0620.0880.1630.0000.0230.0000.0070.0000.0140.0330.0320.0350.0200.0170.0110.0220.0060.0000.0000.0410.0410.0380.0910.0880.1390.1790.0250.0280.0490.1800.3400.3500.3670.0000.2960.1820.5410.2030.3780.2501.0000.2690.1590.1000.1700.1740.0000.0100.0000.0360.0260.0220.0000.0120.0120.0040.0750.0600.0550.1470.0070.0100.0680.0100.0250.0670.1150.0000.0130.0040.0040.1820.0970.2600.1760.0160.1720.3720.0980.0000.0980.0710.1140.1570.0130.000
Grid Production Power StdDev [W]0.0000.0070.0070.0170.0000.0000.0520.0640.0540.1460.2690.1240.1870.2730.0150.0050.0110.0000.0150.0070.0260.0410.0410.0400.0510.0100.0000.0000.0000.0000.0120.0140.0220.1860.1540.1050.2420.0190.0270.0150.2540.2780.2980.3360.0000.3680.3000.3220.7400.3810.3370.2691.0000.2470.1940.1370.1910.0000.0000.0060.0120.0090.0140.0000.0000.0100.0290.1720.1640.0910.2380.0480.0310.1680.0520.0830.0710.0870.0140.0130.0070.0070.2480.1220.2970.2330.0850.1790.3940.1940.0000.1900.1360.0930.2060.0080.003
Grid Production ReactivePower Avg. [W]0.0000.0120.0000.0260.0310.0760.0430.0320.0810.0490.4140.1780.5130.5240.0000.0360.0000.0000.0120.0240.0250.0600.0180.0750.0990.0000.0130.0000.0080.0210.0250.0220.0170.2040.1670.3040.1940.0270.0530.0140.4620.1890.2340.2260.0000.1590.1410.1540.1790.2140.1870.1590.2471.0000.6010.4870.5500.0050.0080.0030.0430.0330.0310.0190.0220.0100.0340.1620.1460.3330.6540.0610.0350.1600.0600.1060.1590.0640.0100.0150.0000.0000.6160.1920.2690.7160.1930.5530.2100.6920.0360.2290.1470.2380.1580.0300.080
Grid Production ReactivePower Max. [W]0.0000.0000.0150.0200.0270.0500.0520.0350.0800.0560.3020.1440.3910.3910.0000.0160.0000.0070.0080.0080.0360.0400.0370.0660.0650.0230.0170.0000.0140.0110.0240.0270.0160.1610.1420.2730.1680.0250.0520.0090.3350.1380.1530.1530.0000.1540.1290.1210.1860.1450.1560.1000.1940.6011.0000.4680.4460.0050.0060.0000.0310.0350.0110.0150.0110.0110.0370.1180.1000.3000.4890.0400.0150.1150.0440.0720.1450.0990.0000.0020.0150.0150.3950.1990.2230.3970.1990.3850.1460.4650.0050.1770.1320.2220.1260.0210.039
Grid Production ReactivePower Min. [W]0.0000.0100.0000.0120.0050.0360.0600.0280.0930.0640.2110.0420.3140.2970.0000.0370.0000.0000.0090.0340.0380.0360.0580.0700.0840.0280.0000.0000.0100.0220.0370.0400.0380.1870.0900.3050.1880.0330.0440.0290.2390.1350.1590.1410.0000.0650.0500.0650.0900.1300.0740.1700.1370.4870.4681.0000.4270.0000.0000.0000.0460.0380.0270.0170.0140.0080.0220.1120.0990.2870.4090.0480.0150.1120.0500.0710.1030.1810.0070.0000.0000.0000.3580.2160.1300.3700.1630.3190.1280.3940.0070.2120.0820.2600.1450.0280.037
Grid Production ReactivePower StdDev [W]0.0000.0050.0000.0130.0240.0250.0220.0340.0760.0530.2400.0830.3530.4570.0000.0270.0080.0060.0310.0000.0440.0340.0320.0680.0600.0120.0070.0000.0060.0000.0040.0000.0160.1450.0800.2200.2590.0260.0460.0200.3160.1330.1590.1570.0000.1240.1270.1790.1460.1490.1320.1740.1910.5500.4460.4271.0000.0030.0000.0030.0140.0160.0080.0000.0000.0070.0210.0950.0830.2800.4650.0360.0170.0940.0330.0650.0790.1210.0110.0130.0000.0000.3880.2080.1840.3820.1840.4790.1540.4330.0410.1440.0790.1610.2470.0270.065
Grid Production VoltagePhase1 Avg. [V]0.0000.0000.0210.0020.0000.0000.0140.0000.0000.0000.0030.0000.0000.0090.0110.0000.0000.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0070.0030.0000.0090.0190.0130.0040.0000.0000.0000.0100.0000.0000.0000.0160.0100.0120.0060.0000.0000.0110.0000.0080.0070.0000.0000.0050.0050.0000.0031.0000.5410.5930.0000.0100.0000.0020.0000.0000.0060.0060.0000.0110.0000.0000.0000.0000.0110.0000.0000.0030.0040.0000.0210.0210.0000.0130.0000.0000.0000.0000.0040.0000.0050.0000.0000.0000.0050.0000.010
Grid Production VoltagePhase2 Avg. [V]0.0000.0000.0210.0000.0000.0000.0170.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.0000.0030.0000.0060.0030.0010.0000.0000.0080.0180.0100.0070.0000.0000.0000.0000.0000.0000.0170.0180.0060.0060.0100.0000.0130.0080.0040.0110.0100.0000.0080.0060.0000.0000.5411.0000.5910.0000.0000.0000.0000.0000.0000.0000.0120.0000.0040.0000.0000.0000.0050.0110.0020.0150.0000.0000.0060.0210.0210.0050.0000.0030.0000.0000.0020.0000.0000.0000.0000.0000.0000.0000.0000.000
Grid Production VoltagePhase3 Avg. [V]0.0000.0040.0200.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0010.0080.0000.0000.0000.0120.0000.0000.0000.0000.0000.0000.0000.0000.0000.0130.0000.0040.0130.0070.0000.0020.0000.0000.0000.0000.0000.0000.0190.0170.0130.0120.0000.0000.0080.0000.0100.0010.0000.0060.0030.0000.0000.0030.5930.5911.0000.0000.0050.0020.0000.0000.0000.0000.0040.0000.0050.0000.0000.0200.0000.0210.0000.0000.0040.0000.0000.0200.0200.0000.0000.0090.0000.0000.0000.0000.0000.0000.0040.0000.0000.0000.0000.000
Grid RotorInvPhase1 Temp. Avg. [°C]0.0000.0060.0000.0000.0200.0000.0210.0290.0320.0170.0480.0000.0360.0270.0000.0170.0000.0320.0140.2470.0590.0750.0400.0310.0150.0240.0170.0190.0170.2050.0780.0790.0940.0270.0330.0330.0250.0090.0280.3300.0210.0440.0530.0490.0000.0180.0080.0080.0000.0360.0370.0360.0120.0430.0310.0460.0140.0000.0000.0001.0000.3440.3150.0040.0150.0000.0000.0200.0210.0090.0180.0000.0000.0210.0060.0040.0220.0040.0000.0100.0000.0000.0270.0100.0150.0410.0290.0000.0300.0050.0040.0270.0320.0350.0120.0000.000
Grid RotorInvPhase2 Temp. Avg. [°C]0.0000.0000.0000.0010.0110.0000.0410.0250.0240.0210.0510.0000.0450.0220.0000.0030.0100.0240.0090.2610.0780.0730.0460.0390.0280.0320.0070.0250.0370.2360.0830.0800.0960.0290.0350.0290.0240.0140.0130.2300.0230.0390.0430.0400.0000.0220.0200.0100.0160.0340.0250.0260.0090.0330.0350.0380.0160.0100.0000.0050.3441.0000.3470.0140.0140.0100.0100.0160.0090.0060.0220.0030.0000.0150.0000.0000.0210.0000.0250.0030.0000.0000.0330.0130.0050.0310.0130.0000.0330.0150.0080.0210.0440.0390.0110.0000.000
Grid RotorInvPhase3 Temp. Avg. [°C]0.0000.0080.0000.0070.0080.0000.0170.0140.0210.0100.0350.0000.0340.0150.0000.0000.0000.0350.0000.3370.0510.0440.0220.0400.0290.0300.0100.0490.0350.3030.0680.0610.0690.0260.0330.0220.0140.0250.0320.1400.0300.0260.0310.0270.0000.0160.0000.0180.0150.0210.0060.0220.0140.0310.0110.0270.0080.0000.0000.0020.3150.3471.0000.0070.0210.0210.0140.0120.0060.0130.0230.0070.0000.0100.0000.0000.0300.0040.0240.0000.0000.0000.0240.0030.0170.0250.0150.0050.0210.0100.0060.0180.0300.0330.0000.0000.005
HVTrafo AirOutlet Temp. Avg. [°C]0.0060.0050.0000.0110.0170.0070.0070.0050.0140.0130.0090.0080.0170.0120.0000.0180.0040.0080.0000.0090.0000.0020.0060.0030.0000.0100.0120.0120.0040.0150.0180.0190.0070.0000.0000.0080.0130.0060.0200.0000.0200.0000.0050.0030.0000.0000.0130.0000.0000.0000.0000.0000.0000.0190.0150.0170.0000.0020.0000.0000.0040.0140.0071.0000.0070.0210.0000.0040.0070.0000.0060.0200.0150.0000.0270.0240.0260.0000.0000.0140.0000.0000.0140.0000.0000.0170.0000.0100.0000.0080.0000.0100.0000.0120.0000.0030.009
HVTrafo Phase1 Temp. Avg. [°C]0.0000.0000.0120.0050.0000.0000.0000.0000.0050.0000.0090.0160.0280.0180.0000.0070.0000.0330.0000.0260.0060.0070.0090.0050.0030.0000.0170.0170.0360.0350.0140.0210.0140.0000.0000.0150.0000.0260.0290.0010.0000.0050.0000.0070.0000.0000.0030.0000.0070.0000.0170.0120.0000.0220.0110.0140.0000.0000.0000.0000.0150.0140.0210.0071.0000.1860.2640.0000.0000.0470.0330.0000.0110.0000.0000.0000.0070.0050.0090.0280.0120.0120.0000.0370.0000.0000.0120.0160.0000.0160.0000.0010.0080.0130.0000.0070.000
HVTrafo Phase2 Temp. Avg. [°C]0.0000.0000.0100.0000.0000.0000.0000.0000.0000.0000.0280.0160.0200.0260.0000.0130.0000.0240.0220.0180.0140.0000.0260.0000.0050.0150.0080.0000.0370.0290.0080.0100.0000.0170.0140.0260.0130.0060.0190.0000.0000.0100.0070.0010.0000.0120.0090.0000.0000.0130.0030.0120.0100.0100.0110.0080.0070.0000.0000.0000.0000.0100.0210.0210.1861.0000.2350.0000.0000.0770.0570.0000.0000.0000.0000.0000.0000.0000.0090.0000.0100.0100.0000.0920.0180.0090.0140.0240.0170.0060.0080.0040.0190.0160.0130.0000.000
HVTrafo Phase3 Temp. Avg. [°C]0.0000.0000.0110.0000.0000.0100.0000.0050.0100.0000.0320.0070.0330.0400.0280.0000.0030.0310.0000.0170.0000.0050.0130.0000.0090.0000.0000.0140.0260.0120.0120.0090.0010.0050.0000.0340.0000.0200.0200.0000.0150.0000.0000.0000.0000.0140.0000.0220.0280.0070.0000.0040.0290.0340.0370.0220.0210.0060.0000.0000.0000.0100.0140.0000.2640.2351.0000.0000.0000.0770.0600.0000.0100.0060.0000.0000.0190.0170.0000.0080.0110.0110.0140.0650.0200.0000.0100.0340.0090.0210.0000.0000.0000.0280.0000.0120.000
HourCounters Average AlarmActive Avg. [h]0.0000.1000.0970.0160.0110.0650.0000.0000.0000.0000.1690.1010.1300.1370.0350.0160.0450.0000.0170.0080.0600.0580.0650.0530.0700.0140.0330.0000.0090.0000.0180.0140.0180.1510.0980.1030.1090.0000.0000.0380.1470.1870.1720.1880.0060.0990.1230.0650.1090.1940.1250.0750.1720.1620.1180.1120.0950.0060.0120.0040.0200.0160.0120.0040.0000.0000.0001.0000.7520.2590.0230.4070.2000.9620.4040.5150.0990.0150.0170.0210.0970.0970.2190.2030.0000.1940.0830.0140.2020.1110.0050.1620.0890.0900.0860.0070.021
HourCounters Average AmbientOk Avg. [h]0.0000.1170.0000.0130.0000.0650.0000.0000.0070.0000.1410.0980.1030.1240.0530.0120.0400.0000.0060.0000.0390.0440.0460.0360.0500.0110.0230.0000.0000.0000.0070.0030.0030.1370.0990.0780.1020.0000.0050.0320.1400.1720.1610.1710.0000.0920.1150.0590.1070.1740.1280.0600.1640.1460.1000.0990.0830.0000.0000.0000.0210.0090.0060.0070.0000.0000.0000.7521.0000.2100.0160.5400.2560.7760.4970.4410.1280.0060.0150.0130.0000.0000.1850.1770.0000.1720.0770.0180.1780.0980.0000.1560.0850.0730.0800.0000.003
HourCounters Average Gen1 Avg. [h]0.0000.0000.0000.0040.0000.0100.0390.0040.0840.0130.1710.0090.2600.2690.0000.0430.0000.0410.0000.0080.0020.0180.0310.0220.0340.0000.0070.0090.0210.0120.0120.0000.0130.0560.0670.1930.0160.0120.0620.0000.0110.0750.0720.0770.0000.0650.0490.0750.0610.0780.0300.0550.0910.3330.3000.2870.2800.0110.0040.0050.0090.0060.0130.0000.0470.0770.0770.2590.2101.0000.5260.0530.0000.2650.0640.1130.0020.0030.0000.0000.0000.0000.0450.6450.3280.0340.3330.1930.0840.2830.0080.0730.0540.1670.0000.0100.010
HourCounters Average Gen2 Avg. [h]0.0000.0000.0000.0220.0230.0600.0670.0270.0920.0340.3750.1700.4390.4410.0000.0410.0000.0140.0120.0260.0180.0600.0150.0920.1110.0190.0160.0000.0200.0200.0000.0000.0000.2120.1800.3910.2040.0350.0930.0110.4880.1160.1380.1680.0010.2220.1730.2170.2140.1890.1740.1470.2380.6540.4890.4090.4650.0000.0000.0000.0180.0220.0230.0060.0330.0570.0600.0230.0160.5261.0000.0280.0140.0260.0140.0210.1620.0620.0100.0040.0000.0000.6190.3100.4750.5520.1330.5310.2020.4970.0440.2370.1630.3150.1570.0370.084
HourCounters Average GridOk Avg. [h]0.0000.1950.0000.0080.0000.0630.0000.0000.0170.0000.0720.0520.0490.0570.0770.0050.0400.0000.0000.0000.0040.0000.0020.0000.0160.0000.0060.0000.0000.0000.0000.0000.0000.0510.0550.0170.0430.0000.0000.0000.0730.0310.0230.0300.0000.0000.0000.0000.0020.0300.0320.0070.0480.0610.0400.0480.0360.0000.0000.0000.0000.0030.0070.0200.0000.0000.0000.4070.5400.0530.0281.0000.4230.4390.7410.6720.0270.0000.0000.0070.0000.0000.0790.0000.0000.0730.0000.0310.0320.0380.0000.0530.0450.0160.0370.0000.000
HourCounters Average GridOn Avg. [h]0.0000.4270.2740.0000.0000.0510.0000.0000.0470.0100.0290.0160.0130.0360.1190.0020.0070.0030.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0120.0050.0000.0090.0000.0150.0230.0000.0000.0000.0270.0160.0140.0150.0080.0000.0060.0000.0070.0150.0110.0100.0310.0350.0150.0150.0170.0000.0000.0200.0000.0000.0000.0150.0110.0000.0100.2000.2560.0000.0140.4231.0000.1540.2790.2650.0560.0000.0000.0000.2740.2740.0550.0000.0000.0440.0000.0110.0260.0230.0320.0180.0000.0170.0220.0000.073
HourCounters Average Run Avg. [h]0.0000.0520.0000.0130.0110.0660.0000.0000.0000.0000.1690.0980.1300.1330.0250.0140.0390.0070.0130.0060.0580.0560.0630.0510.0690.0120.0320.0000.0050.0000.0100.0070.0160.1520.1020.1020.1110.0000.0000.0370.1490.1800.1650.1810.0000.1000.1240.0660.1100.1870.1210.0680.1680.1600.1150.1120.0940.0000.0050.0000.0210.0150.0100.0000.0000.0000.0060.9620.7760.2650.0260.4390.1541.0000.3610.5420.1020.0160.0140.0190.0000.0000.2110.2050.0000.1910.0840.0140.1910.1090.0000.1640.0920.0900.0870.0030.000
HourCounters Average ServiceOn Avg. [h]0.0000.1640.1760.0150.0000.0480.0000.0000.0000.0000.0790.0680.0480.0520.0920.0000.0370.0000.0000.0000.0000.0080.0000.0030.0300.0100.0200.0000.0030.0000.0000.0000.0000.0560.0600.0160.0370.0000.0000.0080.0790.0450.0360.0440.0000.0000.0000.0000.0000.0450.0350.0100.0520.0600.0440.0500.0330.0110.0110.0210.0060.0000.0000.0270.0000.0000.0000.4040.4970.0640.0140.7410.2790.3611.0000.6360.0000.0010.0000.0140.1760.1760.0810.0160.0150.0700.0100.0270.0520.0370.0190.0550.0530.0120.0250.0090.045
HourCounters Average TurbineOk Avg. [h]0.0000.1180.0000.0130.0090.0690.0000.0000.0090.0000.1010.0680.0670.0740.0780.0000.0360.0000.0090.0090.0110.0160.0140.0170.0370.0000.0270.0000.0000.0000.0000.0100.0000.0710.0790.0400.0540.0000.0000.0100.1030.0730.0640.0710.0000.0040.0330.0000.0000.0720.0820.0250.0830.1060.0720.0710.0650.0000.0020.0000.0040.0000.0000.0240.0000.0000.0000.5150.4410.1130.0210.6720.2650.5420.6361.0000.0150.0000.0000.0150.0000.0000.1200.0470.0020.1270.0210.0200.0790.0720.0000.0800.0570.0380.0440.0000.000
HourCounters Average WindOk Avg. [h]0.0000.0160.0000.0230.0550.0270.0440.0460.0390.0020.0970.1730.1020.0990.0000.0000.0110.0150.0000.0150.0350.0240.0210.0120.0080.0000.0340.0090.0040.0300.0250.0240.0200.0260.0270.1260.0450.0200.0210.0060.2800.1590.1280.1210.0000.1240.0550.0700.0690.1230.0450.0670.0710.1590.1450.1030.0790.0000.0150.0000.0220.0210.0300.0260.0070.0000.0190.0990.1280.0020.1620.0270.0560.1020.0000.0151.0000.0320.0130.0030.0000.0000.2510.0010.1060.2120.0560.1580.1340.0870.0010.0420.0160.1140.0140.0340.019
HourCounters Average Yaw Avg. [h]0.0030.0060.0000.0120.0200.0120.0000.0210.0000.0560.0870.0270.0360.0930.0030.0000.0000.0000.0000.0070.0120.0000.0230.0000.0000.0000.0070.0050.0050.0080.0120.0090.0000.0360.0290.0220.0990.0240.0180.0000.0750.0600.0640.0660.0000.0600.0550.0780.0840.0730.0510.1150.0870.0640.0990.1810.1210.0030.0000.0040.0040.0000.0040.0000.0050.0000.0170.0150.0060.0030.0620.0000.0000.0160.0010.0000.0321.0000.0030.0030.0000.0000.0790.0080.0700.0840.0000.0790.0810.0600.0000.0340.0390.0140.0920.0000.000
Hydraulic Oil Temp. Avg. [°C]0.0000.0000.0080.0100.0000.0070.0000.0000.0000.0110.0140.0000.0110.0130.0000.0040.0050.0110.0090.0310.0350.0360.0130.0280.0270.0200.0060.0230.0100.0210.0000.0000.0000.0000.0120.0110.0000.0100.0000.0350.0130.0000.0000.0000.0000.0220.0470.0000.0100.0150.0220.0000.0140.0100.0000.0070.0110.0040.0000.0000.0000.0250.0240.0000.0090.0090.0000.0170.0150.0000.0100.0000.0000.0140.0000.0000.0130.0031.0000.0190.0080.0080.0040.0320.0140.0090.0170.0120.0150.0000.0000.0050.0150.0170.0170.0000.000
Nacelle Temp. Avg. [°C]0.0000.0000.0000.0220.0080.0280.0030.0000.0000.0050.0050.0120.0070.0170.0140.0000.0220.0000.0410.0090.0000.0000.0050.0000.0030.0180.0100.0180.0000.0070.0020.0000.0120.0180.0120.0050.0270.0460.0530.0000.0190.0110.0090.0070.0020.0130.0070.0110.0150.0160.0000.0130.0130.0150.0020.0000.0130.0000.0060.0000.0100.0030.0000.0140.0280.0000.0080.0210.0130.0000.0040.0070.0000.0190.0140.0150.0030.0030.0191.0000.0000.0000.0210.0080.0140.0190.0000.0220.0220.0120.0070.0210.0080.0000.0230.0050.008
Power factor set point0.0000.1400.7500.0000.0000.0110.0000.0000.0130.0000.0000.0000.0000.0000.0180.0060.0090.0070.0000.0000.0040.0030.0060.0000.0000.0000.0000.0080.0080.0000.0290.0080.0060.0000.0000.0000.0000.0000.0000.0000.0050.0080.0070.0080.0320.0000.0000.0000.0000.0080.0050.0040.0070.0000.0150.0000.0000.0210.0210.0200.0000.0000.0000.0000.0120.0100.0110.0970.0000.0000.0000.0000.2740.0000.1760.0000.0000.0000.0080.0001.0000.7500.0270.0000.0000.0030.0000.0000.0340.0000.0000.0000.0000.0000.0000.0040.087
Power factor set point source0.0000.1400.7500.0000.0000.0110.0000.0000.0130.0000.0000.0000.0000.0000.0180.0060.0090.0070.0000.0000.0040.0030.0060.0000.0000.0000.0000.0080.0080.0000.0290.0080.0060.0000.0000.0000.0000.0000.0000.0000.0050.0080.0070.0080.0320.0000.0000.0000.0000.0080.0050.0040.0070.0000.0150.0000.0000.0210.0210.0200.0000.0000.0000.0000.0120.0100.0110.0970.0000.0000.0000.0000.2740.0000.1760.0000.0000.0000.0080.0000.7501.0000.0270.0000.0000.0030.0000.0000.0340.0000.0000.0000.0000.0000.0000.0040.087
Production LatestAverage Active Power Gen 0 Avg. [W]0.0000.0230.0270.0380.0360.0800.0470.0350.0550.0380.3360.2180.3480.3340.0140.0230.0070.0150.0140.0280.0560.0860.0380.1090.1310.0350.0380.0140.0070.0180.0350.0230.0300.2560.1750.3550.2370.0220.0560.0060.5930.2290.2290.2700.0000.1960.1690.1670.1880.3090.2090.1820.2480.6160.3950.3580.3880.0000.0050.0000.0270.0330.0240.0140.0000.0000.0140.2190.1850.0450.6190.0790.0550.2110.0810.1200.2510.0790.0040.0210.0270.0271.0000.0340.1670.7730.0340.4380.3600.4500.0590.2790.1640.2800.1910.0380.103
Production LatestAverage Active Power Gen 1 Avg. [W]0.0000.0000.0000.0110.0040.0000.1080.0480.0660.0100.0920.0000.1620.1650.0000.0180.0000.0330.0060.0000.0550.0590.0300.0460.0300.0170.0090.0000.0120.0000.0000.0110.0050.0530.0000.1630.0140.0140.0530.0260.0050.1950.1870.1930.0000.2690.0920.1190.0990.2670.0600.0970.1220.1920.1990.2160.2080.0130.0000.0000.0100.0130.0030.0000.0370.0920.0650.2030.1770.6450.3100.0000.0000.2050.0160.0470.0010.0080.0320.0080.0000.0000.0341.0000.0180.0200.2610.1040.3090.1940.0070.0590.0000.1420.0140.0060.008
Production LatestAverage Active Power Gen 2 Avg. [W]0.0000.0040.0000.0000.0000.0080.0990.0330.0880.0350.2560.0970.2150.2650.0000.0310.0000.0060.0070.0050.0070.0000.0330.0120.0170.0000.0100.0230.0130.0000.0000.0000.0000.1100.1600.1270.1520.0150.0460.0000.2140.3190.3410.3760.0020.4260.2360.3000.2780.4320.2520.2600.2970.2690.2230.1300.1840.0000.0030.0090.0150.0050.0170.0000.0000.0180.0200.0000.0000.3280.4750.0000.0000.0000.0150.0020.1060.0700.0140.0140.0000.0000.1670.0181.0000.1470.0710.2740.4700.1820.0040.1270.1380.1100.1120.0220.010
Production LatestAverage Reactive Power Gen 0 Avg. [var]0.0000.0160.0030.0320.0400.0940.0370.0340.0400.0320.3210.2310.3130.3200.0070.0270.0000.0250.0110.0240.0480.0840.0320.0990.1250.0230.0410.0110.0030.0190.0420.0350.0350.2570.1920.3160.2380.0200.0530.0180.5630.2210.2720.2630.0000.1720.1560.1620.1820.2520.2210.1760.2330.7160.3970.3700.3820.0000.0000.0000.0410.0310.0250.0170.0000.0090.0000.1940.1720.0340.5520.0730.0440.1910.0700.1270.2120.0840.0090.0190.0030.0030.7730.0200.1471.0000.0420.4110.2500.5490.0620.2820.1730.2460.1960.0450.116
Production LatestAverage Reactive Power Gen 1 Avg. [var]0.0000.0120.0000.0000.0090.0220.0000.0000.0250.0000.1080.0280.1830.1850.0090.0000.0000.0110.0250.0140.0090.0200.0090.0060.0270.0000.0360.0000.0000.0000.0480.0400.0490.0240.0180.0420.0100.0260.0000.0150.0500.0000.0020.0000.0080.0230.0060.0030.0500.0050.0190.0160.0850.1930.1990.1630.1840.0000.0000.0000.0290.0130.0150.0000.0120.0140.0100.0830.0770.3330.1330.0000.0000.0840.0100.0210.0560.0000.0170.0000.0000.0000.0340.2610.0710.0421.0000.0710.0110.6810.0200.0200.0000.0320.0020.0070.022
Production LatestAverage Reactive Power Gen 2 Avg. [var]0.0000.0000.0000.0160.0110.0240.0150.0120.0560.0400.2620.0830.3740.5280.0000.0290.0000.0040.0290.0090.0000.0270.0000.0370.0440.0000.0080.0080.0000.0120.0110.0140.0120.1110.1090.2410.2830.0360.0690.0230.4110.0620.0720.0840.0000.1360.1180.2370.1430.1150.0950.1720.1790.5530.3850.3190.4790.0000.0020.0000.0000.0000.0050.0100.0160.0240.0340.0140.0180.1930.5310.0310.0110.0140.0270.0200.1580.0790.0120.0220.0000.0000.4380.1040.2740.4110.0711.0000.1230.4160.1090.1280.0970.1800.2260.0270.106
Production LatestAverage Total Active Power Avg. [W]0.0000.0100.0340.0210.0050.0060.1930.0860.0840.0480.2150.1240.1420.1630.0120.0140.0000.0000.0000.0140.0910.0680.0680.0590.0430.0330.0160.0050.0070.0000.0380.0450.0460.1740.1340.1360.1590.0090.0350.0540.2600.6110.6180.6720.0000.6500.2930.3430.3130.8540.3670.3720.3940.2100.1460.1280.1540.0040.0000.0000.0300.0330.0210.0000.0000.0170.0090.2020.1780.0840.2020.0320.0260.1910.0520.0790.1340.0810.0150.0220.0340.0340.3600.3090.4700.2500.0110.1231.0000.1530.0000.1880.1200.1220.1360.0050.003
Production LatestAverage Total Reactive Power Avg. [var]0.0000.0000.0000.0140.0140.0400.0310.0250.0640.0280.3110.1330.3860.3770.0000.0180.0000.0000.0210.0060.0180.0310.0190.0710.0990.0090.0000.0000.0020.0170.0040.0000.0100.1660.1110.2380.1370.0370.0430.0000.3240.1240.1580.1570.0000.1140.1000.1070.1460.1530.1240.0980.1940.6920.4650.3940.4330.0000.0000.0000.0050.0150.0100.0080.0160.0060.0210.1110.0980.2830.4970.0380.0230.1090.0370.0720.0870.0600.0000.0120.0000.0000.4500.1940.1820.5490.6810.4160.1531.0000.0140.1770.1140.1850.1110.0180.048
Reactive power generator 0,Total accumulated [var]0.0000.0130.0000.0000.0000.0000.0000.0000.0000.0000.0230.0050.0280.0710.0000.0000.0000.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0100.0000.0000.0070.0000.0380.0000.0430.0550.0000.0170.0060.0490.0000.0040.0020.0000.0020.0060.0000.0090.0000.0080.0000.0000.0360.0050.0070.0410.0050.0000.0000.0040.0080.0060.0000.0000.0080.0000.0050.0000.0080.0440.0000.0320.0000.0190.0000.0010.0000.0000.0070.0000.0000.0590.0070.0040.0620.0200.1090.0000.0141.0000.0430.0000.0330.0410.0010.275
Rotor RPM Avg. [RPM]0.0000.0130.0000.0280.0250.0830.1180.0520.0910.0480.2560.0880.2050.1990.0000.0120.0100.0130.0210.0200.0990.1480.1300.2110.2280.1230.0420.0430.0360.0120.0400.0270.0220.7540.3190.3840.4550.0250.0600.0000.1980.1640.1710.1790.0000.1700.1570.1510.1740.1760.1700.0980.1900.2290.1770.2120.1440.0000.0000.0040.0270.0210.0180.0100.0010.0040.0000.1620.1560.0730.2370.0530.0180.1640.0550.0800.0420.0340.0050.0210.0000.0000.2790.0590.1270.2820.0200.1280.1880.1770.0431.0000.2970.3560.3870.0390.054
Rotor RPM Max. [RPM]0.0000.0000.0000.0130.0190.0750.0770.0800.0460.0330.1880.2220.1150.1230.0060.0070.0200.0000.0080.0240.0690.0900.0700.1010.1030.0830.0500.0100.0000.0180.0120.0170.0100.3470.7960.1360.2920.0070.0390.0130.1410.1040.1160.1150.0060.1300.1500.1170.1690.1110.1460.0710.1360.1470.1320.0820.0790.0000.0000.0000.0320.0440.0300.0000.0080.0190.0000.0890.0850.0540.1630.0450.0000.0920.0530.0570.0160.0390.0150.0080.0000.0000.1640.0000.1380.1730.0000.0970.1200.1140.0000.2971.0000.1100.2150.0240.004
Rotor RPM Min. [RPM]0.0000.0000.0000.0120.0260.0490.0770.0260.1190.0220.1880.0500.2700.2010.0000.0080.0000.0060.0110.0260.0640.1050.0790.1390.1470.0710.0270.0250.0320.0170.0280.0220.0230.3350.1140.7800.2460.0330.0690.0100.1990.0890.0950.1030.0000.0980.0480.1310.0630.1220.0560.1140.0930.2380.2220.2600.1610.0000.0000.0000.0350.0390.0330.0120.0130.0160.0280.0900.0730.1670.3150.0160.0170.0900.0120.0380.1140.0140.0170.0000.0000.0000.2800.1420.1100.2460.0320.1800.1220.1850.0330.3560.1101.0000.1870.0240.058
Rotor RPM StdDev [RPM]0.0040.0180.0000.0140.0140.0420.0480.0410.0660.0790.1710.0550.1460.3220.0060.0190.0000.0210.0310.0080.0860.0930.0850.1080.0900.0810.0220.0190.0000.0020.0230.0190.0130.4150.2400.2160.7000.0370.0290.0000.1780.1080.1130.1150.0000.1410.1740.2000.1970.1310.1520.1570.2060.1580.1260.1450.2470.0050.0000.0000.0120.0110.0000.0000.0000.0130.0000.0860.0800.0000.1570.0370.0220.0870.0250.0440.0140.0920.0170.0230.0000.0000.1910.0140.1120.1960.0020.2260.1360.1110.0410.3870.2150.1871.0000.0390.057
Spinner Temp. Avg. [°C]0.0000.0100.0040.0180.0090.0140.0000.0040.0000.0070.0250.0280.0000.0110.0110.0590.0170.0000.0200.0000.0000.0120.0150.0140.0250.0190.0210.0110.0220.0000.0090.0100.0280.0370.0270.0280.0350.0130.0170.0000.0300.0150.0180.0120.0000.0070.0220.0110.0170.0070.0020.0130.0080.0300.0210.0280.0270.0000.0000.0000.0000.0000.0000.0030.0070.0000.0120.0070.0000.0100.0370.0000.0000.0030.0090.0000.0340.0000.0000.0050.0040.0040.0380.0060.0220.0450.0070.0270.0050.0180.0010.0390.0240.0240.0391.0000.000
Total reactive power [var]0.0000.0350.0870.0000.0000.0000.0070.0000.0000.0000.0420.0150.0550.1010.0000.0000.0000.0070.0000.0050.0000.0180.0000.0160.0060.0050.0000.0000.0000.0000.0000.0050.0000.0500.0060.0680.0770.0000.0210.0040.0810.0040.0060.0050.0000.0050.0030.0000.0010.0080.0120.0000.0030.0800.0390.0370.0650.0100.0000.0000.0000.0000.0050.0090.0000.0000.0000.0210.0030.0100.0840.0000.0730.0000.0450.0000.0190.0000.0000.0080.0870.0870.1030.0080.0100.1160.0220.1060.0030.0480.2750.0540.0040.0580.0570.0001.000

Missing values

2025-05-14T19:37:49.028557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T19:37:49.755057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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72020-01-01 01:10:0000000000000000000000000000000000000000000000000000000110000000000000000000000100000000000000000010000000000000000000000000000000
82020-01-01 01:20:0011110010000000010000100110000000000100000000000000000000000000000000000000000000010000000000000000000000000000000000000000000000
92020-01-01 01:30:0010110010000000100110100100000010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000
TimestampGenerator RPM Max. [RPM]Generator RPM Min. [RPM]Generator RPM Avg. [RPM]Generator RPM StdDev [RPM]Generator Bearing Temp. Avg. [°C]Generator Phase1 Temp. Avg. [°C]Generator Phase2 Temp. Avg. [°C]Generator Phase3 Temp. Avg. [°C]Generator SlipRing Temp. Avg. [°C]Generator Bearing2 Temp. Avg. [°C]Generator CoolingWater Temp. Avg. [°C]Hydraulic Oil Temp. Avg. [°C]Gear Oil Temp. Avg. [°C]Gear Bearing Temp. Avg. [°C]Gear Oil TemperatureBasis Avg. [°C]Gear Oil TemperatureLevel1 Avg. [°C]Gear Oil TemperatureLevel2_3 Avg. [°C]Gear Bearing TemperatureHSRotorEnd Avg. [°C]Gear Bearing TemperatureHSGeneratorEnd Avg. [°C]Gear Bearing TemperatureHSMiddle Avg. [°C]Gear Bearing TemperatureHollowShaftRotor Avg. [°C]Gear Bearing TemperatureHollowShaftGenerator Avg. [°C]Nacelle Temp. Avg. [°C]Rotor RPM Max. [RPM]Rotor RPM Min. [RPM]Rotor RPM Avg. [RPM]Rotor RPM StdDev [RPM]Ambient WindSpeed Max. [m/s]Ambient WindSpeed Min. [m/s]Ambient WindSpeed Avg. [m/s]Ambient WindSpeed StdDev [m/s]Ambient WindDir Relative Avg. [°]Ambient WindDir Absolute Avg. [°]Ambient Temp. Avg. [°C]Ambient WindSpeed Estimated Avg. [m/s]Grid InverterPhase1 Temp. Avg. [°C]Grid RotorInvPhase1 Temp. Avg. [°C]Grid RotorInvPhase2 Temp. Avg. [°C]Grid RotorInvPhase3 Temp. Avg. [°C]Grid Production Power Avg. [W]Grid Production CosPhi Avg.Grid Production Frequency Avg. [Hz]Grid Production VoltagePhase1 Avg. [V]Grid Production VoltagePhase2 Avg. [V]Grid Production VoltagePhase3 Avg. [V]Grid Production CurrentPhase1 Avg. [A]Grid Production CurrentPhase2 Avg. [A]Grid Production CurrentPhase3 Avg. [A]Grid Production Power Max. [W]Grid Production Power Min. [W]Grid Busbar Temp. Avg. [°C]Grid Production Power StdDev [W]Grid Production ReactivePower Avg. [W]Grid Production ReactivePower Max. [W]Grid Production ReactivePower Min. [W]Grid Production ReactivePower StdDev [W]Grid Production PossiblePower Avg. [W]Grid Production PossiblePower Max. [W]Grid Production PossiblePower Min. [W]Grid Production PossiblePower StdDev [W]Grid Production PossibleInductive Avg. [var]Grid Production PossibleInductive Max. [var]Grid Production PossibleInductive Min. [var]Grid Production PossibleInductive StdDev [var]Grid Production PossibleCapacitive Avg. [var]Grid Production PossibleCapacitive Max. [var]Grid Production PossibleCapacitive Min. [var]Grid Production PossibleCapacitive StdDev [var]Active power limit [W]Active power limit sourceReactive power set point [var]Power factor set pointPower factor set point sourceController Ground Temp. Avg. [°C]Controller Top Temp. Avg. [°C]Controller Hub Temp. Avg. [°C]Controller VCP Temp. Avg. [°C]Controller VCP ChokecoilTemp. Avg. [°C]Controller VCP WaterTemp. Avg. [°C]Spinner Temp. Avg. [°C]Spinner Temp. SlipRing Avg. [°C]Blades PitchAngle Min. [°]Blades PitchAngle Max. [°]Blades PitchAngle Avg. [°]Blades PitchAngle StdDev [°]HVTrafo Phase1 Temp. Avg. [°C]HVTrafo Phase2 Temp. Avg. [°C]HVTrafo Phase3 Temp. Avg. [°C]HVTrafo AirOutlet Temp. Avg. [°C]HourCounters Average Total Avg. [h]HourCounters Average GridOn Avg. [h]HourCounters Average GridOk Avg. [h]HourCounters Average TurbineOk Avg. [h]HourCounters Average Run Avg. [h]HourCounters Average Gen1 Avg. [h]HourCounters Average Gen2 Avg. [h]HourCounters Average Yaw Avg. [h]HourCounters Average ServiceOn Avg. [h]HourCounters Average AmbientOk Avg. [h]HourCounters Average WindOk Avg. [h]HourCounters Average AlarmActive Avg. [h]Total hour counter [h]Grid on hours [h]Grid ok hours [h]Turbine ok hours [h]Run hours [h]Generator 1 hours [h]Generator 2 hours [h]Yaw hours [h]Service hours [h]Ambient ok hours [h]Wind ok hours [h]Production LatestAverage Active Power Gen 0 Avg. [W]Production LatestAverage Active Power Gen 1 Avg. [W]Production LatestAverage Active Power Gen 2 Avg. [W]Production LatestAverage Total Active Power Avg. [W]Production LatestAverage Reactive Power Gen 0 Avg. [var]Production LatestAverage Reactive Power Gen 1 Avg. [var]Production LatestAverage Reactive Power Gen 2 Avg. [var]Production LatestAverage Total Reactive Power Avg. [var]Active power generator 0, Total accumulated [W]Active power generator 1, Total accumulated [W]Active power generator 2, Total accumulated [W]Total Active power [W]Reactive power generator 0,Total accumulated [var]Reactive power generator 1, Total accumulated [var]Reactive power generator 2, Total accumulated [var]Total reactive power [var]
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